Commit Graph

379 Commits

Author SHA1 Message Date
slaren
280345968d
cuda : rename build flag to LLAMA_CUDA (#6299) 2024-03-26 01:16:01 +01:00
Pierrick Hymbert
dba1af6129
llama_model_loader: support multiple split/shard GGUFs (#6187)
* split: support in llama_model_loader

* avoid copying the entire vector

Co-authored-by: slaren <slarengh@gmail.com>

* split: move llama_tensor_offset to llama_model_loader

* llama_model_loader: PR feedbacks:
 - use only one gguf_context for metadata only
 - store all ggml_context in a vector as the files and mappings
 - store all weights in a vector along with the source tensor
 - rename ctx_gguf to meta
 - rename ctx_meta to contexts

* avoid copying the entire vector

* Simplify this by making these optional, switch some layer creation tensor optional

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Handle optional tensors

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* llama_model_loader: fail if backend cannot allocate buffer

* fix mmap buffer management

* llama_model_loader: map file to backend buffer if the allocation succeeds only

* llama_model_loader: only map tensors included in the context

* llama_model_loader: minor, use same variable name for consistency, fix spacing in types cast

* llama_model_loader: fail if any of backend buffer cannot be allocated

* spacing

Co-authored-by: slaren <slarengh@gmail.com>

* fix loop over pointer

Co-authored-by: slaren <slarengh@gmail.com>

* llama_model_loader: if n_tensors declared not equals to loaded tensors in split, throw an exception instead of asserting

* llama_model_loader: ensure mappings vector has the expected size

* llama_model_loader:  use at instead of operator[] if this should never add to the map.

* llama_model_loader: immediately add the backend buffer to the model buffers in order to free them if an error occurs in the next allocation. Reserve the expected size.

* llama_model_loader: be sure the model mappings has enough capacity before allocating backend buffer

* llama_model_loader: fix map -> unordered map

* llama_split_prefix: use a clearer version, not pass split path len but dest max len.

Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>

* llama : minor

ggml-ci

* llama : introduce some typedef helpers

* docs: add model shard in hot topic

* llama_model_loader: put mapping in a unique_ptr from the moment it is allocated

Co-authored-by: slaren <slarengh@gmail.com>

* fix llama_split_prefix

---------

Co-authored-by: slaren <slarengh@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
2024-03-22 19:00:01 +01:00
Xiaoyi Chen
29ab270e65
readme : add RecurseChat to the list of UIs (#6219) 2024-03-22 13:29:49 +02:00
Georgi Gerganov
b3e94f26ba
metal : proper assert for mat-mat memory alignment (#6225)
* metal : proper assert for mat-mat memory alignment

ggml-ci

* readme : add notice about the bug fix

* metal : fix the fix

ggml-ci
2024-03-22 11:35:53 +02:00
Xuan Son Nguyen
dfbfdd60f9
readme : add wllama as a wasm binding (#6100) 2024-03-16 17:42:08 +02:00
Andrew Canis
12247f4c69
llama : add Command-R support (#6033)
Information about the Command-R 35B model (128k context) can be found at:
	https://huggingface.co/CohereForAI/c4ai-command-r-v01

Based on the llama2 model with a few changes:

1) New hyper parameter to scale output logits (logit_scale)
2) Uses LayerNorm instead of RMSNorm
3) Transfomer layers have a single shared LayerNorm that feeds into both the
   self-attention and FFN layers in parallel. There is no post-attention LayerNorm.
4) No support for Rotary Position Embeddings (RoPE) scaling
5) No biases used

Find GGUF files here:
	https://huggingface.co/andrewcanis/c4ai-command-r-v01-GGUF

To convert model to GGUF format yourself:

1) Download Command-R Hugging Face safetensors:
	git lfs install
	git clone https://huggingface.co/CohereForAI/c4ai-command-r-v01

2) Run:
	python3 convert-hf-to-gguf.py --outtype f16 ./c4ai-command-r-v01
2024-03-15 22:41:22 +02:00
Linwei Wang
19885d205e
readme : update details about running llama in Termux on Android (#6039) 2024-03-13 20:34:40 +02:00
Georgi Gerganov
76a936c893
readme : update API changes and hot topics 2024-03-13 20:33:56 +02:00
Georgi Gerganov
05b06210c9
llama : more consistent names of count variables (#5994)
* llama : more consistent names of count variables

ggml-ci

* llama : n_parallel -> n_seq_max

* common : fix param name

* examples : fix param name
2024-03-11 17:49:47 +02:00
Georgi Gerganov
d9f65c97c3
readme : update hot topics 2024-03-10 20:58:26 +02:00
Georgi Gerganov
098dbaab44
readme : update hot topics 2024-03-09 18:14:13 +02:00
compilade
c2101a2e90
llama : support Mamba Selective State Space Models (#5328)
* mamba : begin working on support for Mamba SSM

* mamba : begin figuring out how to (ab)use the kv cache for Mamba

* mamba : recurrent inference almost works, but incoherent

* mamba : recurrent inference WORKS!!!

* convert : optionally use d_conv and d_state from config.json for Mamba

* mamba : refactor recurrent conv, resulting in 20% perf increase

It's still slower than I'd like, but I did not really optimize `ggml_exp` yet.

I also refactored `ggml_exp` to work with tensors with more than 2 dimensions.

* ggml : parallelize ggml_exp

This results in 8% faster token generation for Mamba-130M.

* mamba : simplify the conv step with a self-overlapping view

Turns out the conv_state can be made smaller by one column.
Note that this breaks existing GGUFs of Mamba,
because the key_value_length field is tied to the conv_state size.

Convolution with a self-overlapping view is cool!
And it's much simpler than what I initially thought would be necessary
to make the convolution step work with more than 1 token at a time.

Next step is to make the SSM step work on batches of tokens too,
and thus I need to figure out a way to make a parallel selective scan
which will keep the ssm_state small and won't make it bigger
by a factor of (n_layer * batch_size).

* llama : fix Mamba KV self size wrongly displaying as f16 instead of f32

Relatedly, I also tried to see if other types than f32 worked for the states,
but they don't, because of the operators used.
It's probably better anyway to keep lots of precision there,
since the states are small anyway.

* mamba : fix self-overlapping view depth stride

* mamba : handle batches of more than 1 token

This means running Mamba no longer crashes when using the default settings!
And probably also slightly faster prompt processing.
Both batched and non-batched processing yield the same output.

Previously, the state was not cleared when starting a sequence.
Next step is to make the KV cache API work as expected for Mamba models.

* ggml: add ggml_ssm_scan to help with parallel selective scan

If the selective scan was implemented without a custom operator,
there would be waaay too many nodes in the graph. For example,
for Mamba-130M, with a batch size of 512 (the default),
a naive selective scan could add at least 24*512=12288 nodes,
which is more than LLAMA_MAX_NODES (8192),
and that's only for the smallest Mamba model.
So it's much cleaner with a custom operator.
Not sure about the name, though.

* ggml : in ggml_ssm_scan, merge multiple rows in the same vec operation

This will help with performance on CPU if ggml_vec_mul_f32
and ggml_vec_add_f32 are ever optimized with SIMD.

* mamba : very basic quantization support

Mostly works, but there is currently no difference
between the variants of a k-quant (e.g. Q4_K_S and Q4_K_M are the same).
Most of the SSM-specific weights can be kept in f32 without affecting
the size that much, since they are relatively small.
(the linear projection weights are responsible for most of Mamba's size)

Too much quantization seems to make the state degrade quite fast, and
the model begins to output gibberish.
It seems to affect bigger models to a lesser extent than small models,
but I'm not sure by how much.

Experimentation will be needed to figure out which weights are more important
for the _M (and _L?) variants of k-quants for Mamba.

* convert : fix wrong name for layer norm weight of offical Mamba models

I was using Q-bert/Mamba-* models before, which have a slighlty different
naming scheme for the weights.
(they start with "model.layers" instead of "backbone.layers")

* mamba : fuse more steps of the SSM scan in the ggml_ssm_scan operator

This increases performance on CPU by around 30% for prompt processing,
and by around 20% for text generation.

However, it also makes the ggml_exp and ggml_soft_plus operators unused.
Whether or not they should be kept will be decided later.

* convert : for Mamba, also consider the "MambaLMHeadModel" arch name

It's the name of the class of the official implementation,
though they don't use it (yet) in the "architectures" field of config.json

* mamba : fix vocab size problems with official models

The perplexity was waaaay to high for models with a non-round vocab size.
Not sure why, but it needed to be fixed in the metadata.

Note that this breaks existing GGUF-converted Mamba models,
but **only if** the vocab size was not already rounded.

* ggml : remove ggml_exp and ggml_soft_plus

They did not exist anyway outside of this branch,
and since ggml_ssm_scan fused operations together, they are unused.
It's always possible to bring them back if needed.

* mamba : remove some useless comments

No code change.

* convert : fix flake8 linter errors

* mamba : apply suggestions from code review

* mamba : remove unecessary branch for row-wise ssm_state and C multiplication

It was previously done to avoid permuting when only one token is processed
at a time (like when generating text), but permuting is cheap,
and dynamically changing the compute graph is not future-proof.

* ggml : in ggml_ssm_scan, use more appropriate asserts

* ggml : rename the destination pointer in ggml_compute_forward_ssm_scan_f32

* mamba : multiple sequences, but one at a time

This is a step towards making this Mamba implementation usable
with the server example (the way the system prompt is kept when clearing
the client slots will need to be changed before this can work, though).

The KV cache size for this kind of model is tied to the maximum number
of sequences kept at any single time.
For now, this number is obtained from n_parallel (plus one,
to have an extra sequence to dedicate to the system prompt),
but there might be a better way to do this which won't also
make the main example use 2 cells even if only 1 is really used.
(for this specific case, --parallel 0 helps)

Simultaneous sequence processing will probably require changes to
ggml_ssm_scan, and possibly a new operator for the conv step.

* mamba : support llama_kv_cache_seq_cp

This (mis)uses the logic around K shifts, because tokens in a state
can't be shifted anyway, and because inp_K_shift has the right shape and type.
Using ggml_get_rows is a nice way to do copies, but copy chains can't work.
Fortunately, copy chains don't really seem to be used in the examples.

Each KV cell is dedicated to the sequence ID corresponding to its own index.

* mamba : use a state mask

It's cleaner than the previous heuristic of
checking for the pos of the first token in the batch.

inp_KQ_mask could not be re-used for this, because it has the wrong shape
and because it seems more suited to the next step of
simultaneous sequence processing (helping with the problem of
remembering which token belongs to which sequence(s)/state(s)).

* llama : replace the usage of n_ctx with kv_self.size in many places

* mamba : use n_tokens directly instead of n_tok

* mamba : in comments, properly refer to KV cells instead of slots

* mamba : reduce memory usage of ggml_ssm_scan

From 290.37 MiB to 140.68 MiB of CPU compute buffer size
with Mamba 3B with a batch size of 512.

The result tensor of ggml_ssm_scan was previously a big part
of the CPU compute buffer size. To make it smaller,
it does not contain the intermediate ssm states anymore.
Both y and the last ssm state are combined in the result tensor,
because it seems only a single tensor can be returned by an operator
with the way the graph is built.

* mamba : simultaneous sequence processing

A batch can now contain tokens from multiple sequences.

This is necessary for at least the parallel example, the server example,
and the HellaSwag test in the perplexity example.

However, for this to be useful, uses of llama_kv_cache_seq_rm/cp
will need to be changed to work on whole sequences.

* ggml : add ggml_ssm_conv as a new operator for the conv step of Mamba

This operator makes it possible to use and update the correct states
for each token of the batch in the same way as ggml_ssm_scan.
Other solutions which use existing operators would need loops which would
add too many nodes to the graph (at least the ones I thought of).

Using this operator further reduces the size of the CPU compute buffer
from 140.68 MiB to 103.20 MiB with Mamba 3B with a batch size of 512.
And (at least on CPU), it's a bit faster than before.

Note that "ggml_ssm_conv" is probably not the most appropriate name,
and it could be changed if a better one is found.

* llama : add inp_s_seq as a new input tensor

The most convenient implementation to select the correct state (for Mamba)
for each token is to directly get the correct index from a tensor.
This is why inp_s_seq is storing int32_t and not floats.

The other, less convenient way to select the correct state would be
to have inp_KQ_mask contain 1.0f for each state used by a token
and 0.0f otherwise. This complicates quickly fetching the first used
state of a token, and is also less efficient because a whole row
of the mask would always need to be read for each token.

Using indexes makes it easy to stop searching when there are
no more sequences for a token, and the first sequence assigned
is always very quickly available (it's the first element of each row).

* mamba : support llama_kv_cache_seq_cp copy chains

* mamba : support shifting and dividing the kv cache pos

* mamba : make the server and parallel examples work with whole sequences

A seq_id is dedicated to the system prompt in both cases.

* llama : make llama_kv_cache_seq_rm return whether it succeeded or not

* mamba : dedicate an input tensor for state copy indices

This is cleaner and makes it easier to adapt when/if token positions
(and by extension, inp_K_shift) are no longer integers.

* mamba : adapt perplexity, batched, and batched-bench examples

* perplexity : limit the max number of sequences

This adapts to what the loaded model can provide.

* llama : add llama_n_max_seq to get the upper limit for seq_ids

Used by the perplexity example.

* batched : pass n_parallel to the model's context params

This should have been there already, but it wasn't.

* batched-bench : reserve sequences to support Mamba

* batched-bench : fix tokens being put in wrong sequences

Generation quality isn't what's measured in there anyway,
but at least using the correct sequences avoids using non-consecutive
token positions.

* mamba : stop abusing attention metadata

This breaks existing converted-to-GGUF Mamba models,
but will allow supporting mixed architectures like MambaFormer
without needing to break Mamba models.

This will also allow changing the size of Mamba's states
without having to reconvert models in the future.
(e.g. using something else than d_conv - 1 columns for the conv_states
 will not require breaking existing converted Mamba models again)

* gguf-py : add new KV metadata key-value pairs for Mamba

* llama : add new metadata key-value pairs for Mamba

* llama : guard against divisions by zero when n_head is 0

* mamba : rename "unlimited" KV cache property to "recurrent"

* mamba : more correctly update the "used" field of the KV cache

* ggml : in ggml_ssm_scan, use a threshold for soft_plus

This is how the official Mamba implementation does it,
and it's also what torch.nn.Softplus does.

* convert : for Mamba, fallback to internal NeoX tokenizer

The resulting models are exactly the same
as if the tokenizer.json and tokenizer_config.json of GPT-NeoX were there.

* mamba : support state saving and restoring

* ggml : implicitly pass src tensors through dst for Mamba-related ops

* mamba : clarify some comments

* server : fix cache_tokens not getting correctly resized

Otherwise, when the "we have to evaluate at least 1 token" special case
was triggered, an extra token was kept in cache_tokens even if it was
removed from the KV cache.

For Mamba, this caused useless prompt reprocessing when the previous
request triggered the above case.

* convert-hf : support new metadata keys for Mamba

For the models available at
https://huggingface.co/collections/state-spaces/transformers-compatible-mamba-65e7b40ab87e5297e45ae406

* mamba : rename metadata to be more similar to transformers library

This breaks existing converted-to-GGUF models,
but the metadata names are more "standard".

* mamba : support mamba-*-hf models

These models share their token_embd.weight with their output.weight

* mamba : add missing spaces

This is purely a formatting change.

* convert-hf : omit output.weight when identical with token_embd.weight

Only for Mamba for now, but it might be relevant for other models eventually.
Most Mamba models actually share these two tensors, albeit implicitly.

* readme : add Mamba to supported models, and add recent API changes

* mamba : move state_seq and state_mask views outside layer loop

A few tensors were also missing `struct` in front of `ggml_tensor`.
2024-03-08 17:31:00 -05:00
Georgi Gerganov
29ae62d2ae
llama : fix embeddings (#5796)
* llama : fix embeddings

ggml-ci

* llama : do not use KV cache for non-causal models

ggml-ci

* embeddings : fix llama_batch_init arg

* llama : add pooling switch

* llama : distinguish token vs sequence embeddings

ggml-ci

* llama : assert pooling tensor

* llama : simplify causal mask condition

ggml-ci

* llama : assert input batch with pooling enabled

* readme : update API changes list
2024-03-04 22:31:20 +02:00
Georgi Gerganov
231ae28f07
readme : add API changes section 2024-03-03 12:44:03 +02:00
Jared Van Bortel
4d4d2366fc
convert : automatically fall back to HfVocab if tokenizer.model doesn't exist (#5821) 2024-03-02 12:27:26 -05:00
Georgi Gerganov
38d16b1426
server : remove api_like_OAI.py proxy script (#5808) 2024-03-01 20:00:58 +02:00
Daniel Bevenius
6c4416868d
readme : add link to LLaVA 1.6 models (#5758)
Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
2024-02-28 10:39:39 +02:00
Artem
c4d7f81786
readme : update ui list (#5731)
* Add LLMFarm (ui for iOS) to list
2024-02-26 16:15:28 +02:00
Pierrick Hymbert
8b350356b2
server: docs - refresh and tease a little bit more the http server (#5718)
* server: docs - refresh and tease a little bit more the http server

* Rephrase README.md server doc

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Update examples/server/README.md

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Update examples/server/README.md

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Update README.md

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-02-25 21:46:29 +01:00
Ashok Gelal
7d548a1827
readme : add Msty to UI list (#5618) 2024-02-25 17:57:34 +02:00
Georgi Gerganov
56d03d92be
readme : update hot topics 2024-02-22 10:35:54 +02:00
Ettore Di Giacinto
a00a35cef9
readme : add LocalAI to the availables UI (#5629) 2024-02-21 16:39:10 +02:00
Georgi Gerganov
c14f72db9c
readme : update hot topics 2024-02-21 15:39:54 +02:00
postmasters
580111d42b
llama : add gemma model (#5631)
There are couple things in this architecture:

1. Shared input and output embedding parameters.
2. Key length and value length are not derived from `n_embd`.

More information about the models can be found at
https://ai.google.dev/gemma. GGUFs can be downloaded from
https://huggingface.co/google.
2024-02-21 15:08:22 +02:00
Dane Madsen
5207b3fbc5
readme : update UI list (#5605)
* Add maid to ui list

* Specify licence
2024-02-20 12:00:23 +02:00
Mirko185
769a716e30
readme : update (#5572)
Added 1.5-bit on README.md
2024-02-19 09:39:31 +02:00
Georgi Gerganov
b1de96824b
ci : fix wikitext url + compile warnings (#5569)
ggml-ci
2024-02-18 22:39:30 +02:00
Rune
594fca3fef
readme : fix typo (#5490)
executabhle -> executable
2024-02-14 17:15:49 +02:00
Marko Tasic
e4124c2477
readme : add JavaScript/Wasm repo (#5415) 2024-02-09 12:17:00 +02:00
Ebey Abraham
8c933b70c2
fix typo in readme (#5399)
Co-authored-by: Ebey Abraham <ebeyabraham@microsoft.com>
2024-02-07 22:11:30 +01:00
Kamil Tomšík
b906596bb7
Add Ava in the list of llama.cpp UIs (#4362) 2024-02-07 13:44:52 -05:00
Eve
ed0bf32290
readme : modernize (#5379)
* first cleanup, update everything to Llama 2 and remove outdated content

* Delete SHA256SUMS

* make build instructions generic

* recommend Q4_K_M quantization method

* Update README.md
2024-02-07 08:21:30 +02:00
Ben Williams
9a697d842b
readme : update ui list (#5354) 2024-02-07 08:16:48 +02:00
Kawrakow
b08f22c882
Update README.md (#5366)
Add some links to quantization related PRs
2024-02-06 19:00:16 +02:00
BarfingLemurs
2e9c0bd6b3
readme : add phi, orion 14b, internlm2, and yi-VL to readme (#5362) 2024-02-06 16:06:48 +02:00
Johannes Gäßler
78b00dda6c
README: updated introduction (#5343)
* README: updated introduction

* readme : update

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-02-05 15:55:10 +01:00
chiranko
5d55b0cd82
readme : add CodeShell models to the supported models list (#5330) 2024-02-05 09:41:38 +02:00
BADR
6a66c5071a
readme : add tenere in the ui tools list (#5284) 2024-02-03 13:20:26 +02:00
Xuan Son Nguyen
6b91b1e0a9
docker : add build for SYCL, Vulkan + update readme (#5228)
* add vulkan dockerfile

* intel dockerfile: compile sycl by default

* fix vulkan dockerfile

* add docs for vulkan

* docs: sycl build in docker

* docs: remove trailing spaces

* docs: sycl: add docker section

* docs: clarify install vulkan SDK outside docker

* sycl: use intel/oneapi-basekit docker image

* docs: correct TOC

* docs: correct docker image for Intel oneMKL
2024-02-02 09:56:31 +02:00
Georgi Gerganov
5cb04dbc16
llama : remove LLAMA_MAX_DEVICES and LLAMA_SUPPORTS_GPU_OFFLOAD (#5240)
* llama : remove LLAMA_MAX_DEVICES from llama.h

ggml-ci

* Update llama.cpp

Co-authored-by: slaren <slarengh@gmail.com>

* server : remove LLAMA_MAX_DEVICES

ggml-ci

* llama : remove LLAMA_SUPPORTS_GPU_OFFLOAD

ggml-ci

* train : remove LLAMA_SUPPORTS_GPU_OFFLOAD

* readme : add deprecation notice

* readme : change deprecation notice to "remove" and fix url

* llama : remove gpu includes from llama.h

ggml-ci

---------

Co-authored-by: slaren <slarengh@gmail.com>
2024-01-31 17:30:17 +02:00
Neo Zhang Jianyu
01684139c3
support SYCL backend windows build (#5208)
* support SYCL backend windows build

* add windows build in CI

* add for win build CI

* correct install oneMKL

* fix install issue

* fix ci

* fix install cmd

* fix install cmd

* fix install cmd

* fix install cmd

* fix install cmd

* fix win build

* fix win build

* fix win build

* restore other CI part

* restore as base

* rm no new line

* fix no new line issue, add -j

* fix grammer issue

* allow to trigger manually, fix format issue

* fix format

* add newline

* fix format

* fix format

* fix format issuse

---------

Co-authored-by: Abhilash Majumder <30946547+abhilash1910@users.noreply.github.com>
2024-01-31 08:08:07 +05:30
Romain Neutron
5589921ef8
readme : minor (#5204)
This is about tuning the code formatting of the README file
2024-01-30 11:16:38 +02:00
Georgi Gerganov
49f44b5c55
readme : update hot topics 2024-01-30 11:14:44 +02:00
Abhilash Majumder
0f648573dd
ggml : add unified SYCL backend for Intel GPUs (#2690)
* first update for migration

* update init_cublas

* add debug functio, commit all help code

* step 1

* step 2

* step3 add fp16, slower 31->28

* add GGML_LIST_DEVICE function

* step 5 format device and print

* step6, enhance error check, remove CUDA macro, enhance device id to fix none-zero id issue

* support main device is non-zero

* step7 add debug for code path, rm log

* step 8, rename all macro & func from cuda by sycl

* fix error of select non-zero device, format device list

* ren ggml-sycl.hpp -> ggml-sycl.h

* clear CMAKE to rm unused lib and options

* correct queue: rm dtct:get_queue

* add print tensor function to debug

* fix error: wrong result in 658746bb26702e50f2c59c0e4ada8e9da6010481

* summary dpct definition in one header file to replace folder:dpct

* refactor device log

* mv dpct definition from folder dpct to ggml-sycl.h

* update readme, refactor build script

* fix build with sycl

* set nthread=1 when sycl, increase performance

* add run script, comment debug code

* add ls-sycl-device tool

* add ls-sycl-device, rm unused files

* rm rear space

* dos2unix

* Update README_sycl.md

* fix return type

* remove sycl version from include path

* restore rm code to fix hang issue

* add syc and link for sycl readme

* rm original sycl code before refactor

* fix code err

* add know issue for pvc hang issue

* enable SYCL_F16 support

* align pr4766

* check for sycl blas, better performance

* cleanup 1

* remove extra endif

* add build&run script, clean CMakefile, update guide by review comments

* rename macro to intel hardware

* editor config format

* format fixes

* format fixes

* editor format fix

* Remove unused headers

* skip build sycl tool for other code path

* replace tab by space

* fix blas matmul function

* fix mac build

* restore hip dependency

* fix conflict

* ren as review comments

* mv internal function to .cpp file

* export funciton print_sycl_devices(), mv class dpct definition to source file

* update CI/action for sycl code, fix CI error of repeat/dup

* fix action ID format issue

* rm unused strategy

* enable llama_f16 in ci

* fix conflict

* fix build break on MacOS, due to CI of MacOS depend on external ggml, instead of internal ggml

* fix ci cases for unsupported data type

* revert unrelated changed in cuda cmake
remove useless nommq
fix typo of GGML_USE_CLBLAS_SYCL

* revert hip cmake changes

* fix indent

* add prefix in func name

* revert no mmq

* rm cpu blas duplicate

* fix no_new_line

* fix src1->type==F16 bug.

* pass batch offset for F16 src1

* fix batch error

* fix wrong code

* revert sycl checking in test-sampling

* pass void as arguments of ggml_backend_sycl_print_sycl_devices

* remove extra blank line in test-sampling

* revert setting n_threads in sycl

* implement std::isinf for icpx with fast math.

* Update ci/run.sh

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Update examples/sycl/run-llama2.sh

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Update examples/sycl/run-llama2.sh

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Update CMakeLists.txt

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Update CMakeLists.txt

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Update CMakeLists.txt

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Update CMakeLists.txt

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* add copyright and MIT license declare

* update the cmd example

---------

Co-authored-by: jianyuzh <jianyu.zhang@intel.com>
Co-authored-by: luoyu-intel <yu.luo@intel.com>
Co-authored-by: Meng, Hengyu <hengyu.meng@intel.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-01-28 17:56:23 +02:00
Marcus Dunn
af4980bfed
readme : add link to rust bindings (#5148)
* added link to another set of rust bindings with brief note on differences.

* fixed link name
2024-01-28 10:30:44 +02:00
Kyle Mistele
39baaf55a1
docker : add server-first container images (#5157)
* feat: add Dockerfiles for each platform that user ./server instead of ./main

* feat: update .github/workflows/docker.yml to build server-first docker containers

* doc: add information about running the server with Docker to README.md

* doc: add information about running with docker to the server README

* doc: update n-gpu-layers to show correct GPU usage

* fix(doc): update container tag from `server` to `server-cuda` for README example on running server container with CUDA
2024-01-28 09:55:31 +02:00
Georgi Gerganov
aad0b01d73
readme : update hot topics 2024-01-26 10:52:33 +02:00
XiaotaoChen
fe54033b69
readme : add MobileVLM 1.7B/3B to the supported models list (#5107)
Co-authored-by: Chenxiaotao03 <chenxiaotao03@meituan.com>
2024-01-25 22:14:32 +02:00
adel boussaken
48e2b13372
Add a dart/flutter binding to README.md (#4882) 2024-01-20 03:05:43 -05:00
iohub
18adb4e9bb
readme : add 3rd party collama reference to UI list (#4840)
Add a VSCode extension for llama.cpp reference to UI list
2024-01-09 18:45:54 +02:00
Georgi Gerganov
a9a8c5de3d
readme : add link to SOTA models 2024-01-08 20:25:17 +02:00
Lars Grammel
b7e7982953
readme : add lgrammel/modelfusion JS/TS client for llama.cpp (#4814) 2024-01-07 22:24:11 +02:00
automaticcat
24a447e20a
ggml : add ggml_cpu_has_avx_vnni() (#4589)
* feat: add avx_vnni based on intel documents

* ggml: add avx vnni based on intel document

* llama: add avx vnni information display

* docs: add more details about using oneMKL and oneAPI for intel processors

* docs: add more details about using oneMKL and oneAPI for intel processors

* docs: add more details about using oneMKL and oneAPI for intel processors

* docs: add more details about using oneMKL and oneAPI for intel processors

* docs: add more details about using oneMKL and oneAPI for intel processors

* Update ggml.c

Fix indentation upgate

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-12-30 10:07:48 +02:00
manikbhandari
ea5497df5d
gpt2 : Add gpt2 architecture integration (#4555) 2023-12-28 15:03:57 +01:00
Paul Tsochantaris
a206137f92
Adding Emeltal reference to UI list (#4629) 2023-12-25 18:09:53 +02:00
Shintarou Okada
753be377b6
llama : add PLaMo model (#3557)
* add plamo mock

* add tensor loading

* plamo convert

* update norm

* able to compile

* fix norm_rms_eps hparam

* runnable

* use inp_pos

* seems ok

* update kqv code

* remove develop code

* update README

* shuffle attn_q.weight and attn_output.weight for broadcasting

* remove plamo_llm_build_kqv and use llm_build_kqv

* fix style

* update

* llama : remove obsolete KQ_scale

* plamo : fix tensor names for correct GPU offload

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-12-24 15:35:49 +02:00
FantasyGmm
a55876955b
cuda : fix jetson compile error (#4560)
* fix old jetson compile error

* Update Makefile

* update jetson detect and cuda version detect

* update cuda marco define

* update makefile and cuda,fix some issue

* Update README.md

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Update Makefile

* Update README.md

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-12-22 17:11:12 +02:00
Michael Kesper
28cb35a0ec
make : add LLAMA_HIP_UMA option (#4587)
NB: LLAMA_HIP_UMA=1 (or any value) adds MK_CPPFLAG -DGGML_HIP_UMA
2023-12-22 10:03:25 +02:00
Deins
2bb98279c5
readme : add zig bindings (#4581) 2023-12-22 08:49:54 +02:00
Erik Garrison
0f630fbc92
cuda : ROCm AMD Unified Memory Architecture (UMA) handling (#4449)
* AMD ROCm: handle UMA memory VRAM expansions

This resolves #2797 by allowing ROCm AMD GPU users with a UMA to
dynamically expand the VRAM allocated to the GPU.

Without this, AMD ROCm users with shared CPU/GPU memory usually are
stuck with the BIOS-set (or fixed) framebuffer VRAM, making it
impossible to load more than 1-2 layers.

Note that the model is duplicated in RAM because it's loaded once for
the CPU and then copied into a second set of allocations that are
managed by the HIP UMA system. We can fix this later.

* clarify build process for ROCm on linux with cmake

* avoid using deprecated ROCm hipMallocHost

* keep simplifying the change required for UMA

* cmake: enable UMA-compatible allocation when LLAMA_HIP_UMA=ON
2023-12-21 21:45:32 +02:00
Georgi Gerganov
c083718c89
readme : update coding guidelines 2023-12-21 19:27:14 +02:00
Georgi Gerganov
b1306c4394
readme : update hot topics 2023-12-17 20:16:23 +02:00
BarfingLemurs
0353a18401
readme : update supported model list (#4457) 2023-12-14 09:38:49 +02:00
Georgi Gerganov
113f9942fc
readme : update hot topics 2023-12-13 14:05:38 +02:00
Georgi Gerganov
bcc0eb4591
llama : per-layer KV cache + quantum K cache (#4309)
* per-layer KV

* remove unnecessary copies

* less code duplication, offload k and v separately

* llama : offload KV cache per-layer

* llama : offload K shift tensors

* llama : offload for rest of the model arches

* llama : enable offload debug temporarily

* llama : keep the KV related layers on the device

* llama : remove mirrors, perform Device -> Host when partial offload

* common : add command-line arg to disable KV cache offloading

* llama : update session save/load

* llama : support quantum K cache (#4312)

* llama : support quantum K cache (wip)

* metal : add F32 -> Q8_0 copy kernel

* cuda : add F32 -> Q8_0 copy kernel

ggml-ci

* cuda : use mmv kernel for quantum cache ops

* llama : pass KV cache type through API

* llama : fix build

ggml-ci

* metal : add F32 -> Q4_0 copy kernel

* metal : add F32 -> Q4_1 copy kernel

* cuda : wip

* cuda : add F32 -> Q4_0 and F32 -> Q4_1 copy kernels

* llama-bench : support type_k/type_v

* metal : use mm kernel only for quantum KV cache

* cuda : add comment

* llama : remove memory_f16 and kv_f16 flags

---------

Co-authored-by: slaren <slarengh@gmail.com>

* readme : add API change notice

---------

Co-authored-by: slaren <slarengh@gmail.com>
2023-12-07 13:03:17 +02:00
vodkaslime
524907aa76
readme : fix (#4135)
* fix: readme

* chore: resolve comments

* chore: resolve comments
2023-11-30 23:49:21 +02:00
Dawid Wysocki
74daabae69
readme : fix typo (#4253)
llama.cpp uses GitHub Actions, not Gitlab Actions.
2023-11-30 23:43:32 +02:00
Peter Sugihara
4fea3420ee
readme : add FreeChat (#4248) 2023-11-29 09:16:34 +02:00
Kasumi
0dab8cd7cc
readme : add Amica to UI list (#4230) 2023-11-27 19:39:42 +02:00
Georgi Gerganov
9656026b53
readme : update hot topics 2023-11-26 20:42:51 +02:00
Georgi Gerganov
04814e718e
readme : update hot topics 2023-11-25 12:02:13 +02:00
Aaryaman Vasishta
b35f3d0def
readme : use PATH for Windows ROCm (#4195)
* Update README.md to use PATH for Windows ROCm

* Update README.md

* Update README.md
2023-11-24 09:52:39 +02:00
Georgi Gerganov
d103d935c0
readme : update hot topics 2023-11-23 13:51:22 +02:00
Aaryaman Vasishta
dfc7cd48b1
readme : update ROCm Windows instructions (#4122)
* Update README.md

* Update README.md

Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>

---------

Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>
2023-11-20 17:02:46 +02:00
Galunid
36eed0c42c
stablelm : StableLM support (#3586)
* Add support for stablelm-3b-4e1t
* Supports GPU offloading of (n-1) layers
2023-11-14 11:17:12 +01:00
Georgi Gerganov
c049b37d7b
readme : update hot topics 2023-11-13 14:18:08 +02:00
Richard Kiss
532dd74e38
Fix some documentation typos/grammar mistakes (#4032)
* typos

* Update examples/parallel/README.md

Co-authored-by: Kerfuffle <44031344+KerfuffleV2@users.noreply.github.com>

---------

Co-authored-by: Kerfuffle <44031344+KerfuffleV2@users.noreply.github.com>
2023-11-11 23:04:58 -07:00
Georgi Gerganov
224e7d5b14
readme : add notice about #3912 2023-11-02 20:44:12 +02:00
Ian Scrivener
5a42a5f8e8
readme : remove unsupported node.js library (#3703)
- https://github.com/Atome-FE/llama-node is quite out of date
- doesn't support recent/current llama.cpp functionality
2023-10-22 21:16:43 +03:00
Georgi Gerganov
d1031cf49c
sampling : refactor init to use llama_sampling_params (#3696)
* sampling : refactor init to use llama_sampling_params

* llama : combine repetition, frequency and presence penalties in 1 call

* examples : remove embd-input and gptneox-wip

* sampling : rename penalty params + reduce size of "prev" vector

* sampling : add llama_sampling_print helper

* sampling : hide prev behind API and apply #3661

ggml-ci
2023-10-20 21:07:23 +03:00
Georgi Gerganov
004797f6ac
readme : update hot topics 2023-10-18 21:44:43 +03:00
BarfingLemurs
8402566a7c
readme : update hot-topics & models, detail windows release in usage (#3615)
* Update README.md

* Update README.md

* Update README.md

* move "Running on Windows" section below "Prepare data and run"

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-10-17 21:13:21 +03:00
ldwang
5fe268a4d9
readme : add Aquila2 links (#3610)
Signed-off-by: ldwang <ftgreat@gmail.com>
Co-authored-by: ldwang <ftgreat@gmail.com>
2023-10-17 18:52:33 +03:00
Ian Scrivener
f3040beaab
typo : it is --n-gpu-layers not --gpu-layers (#3592)
fixed a typo in the MacOS Metal run doco
2023-10-12 14:10:50 +03:00
Galunid
9f6ede19f3
Add MPT model to supported models in README.md (#3574) 2023-10-10 19:02:49 -04:00
Xingchen Song(宋星辰)
c5b49360d0
readme : add bloom (#3570) 2023-10-10 19:28:50 +03:00
BarfingLemurs
1faaae8c2b
readme : update models, cuda + ppl instructions (#3510) 2023-10-06 22:13:36 +03:00
Georgi Gerganov
beabc8cfb0
readme : add project status link 2023-10-04 16:50:44 +03:00
slaren
40e07a60f9
llama.cpp : add documentation about rope_freq_base and scale values (#3401)
* llama.cpp : add documentation about rope_freq_base and scale values

* add notice to hot topics
2023-09-29 18:42:32 +02:00
BarfingLemurs
0a4a4a0982
readme : update hot topics + model links (#3399) 2023-09-29 15:50:35 +03:00
Andrew Duffy
569550df20
readme : add link to grammars app (#3388)
* Add link to grammars app per @ggernagov suggestion

Adding a sentence in the Grammars section of README to point to grammar app, per https://github.com/ggerganov/llama.cpp/discussions/2494#discussioncomment-7138211

* Update README.md
2023-09-29 14:15:57 +03:00
Pierre Alexandre SCHEMBRI
4aea3b846e
readme : add Mistral AI release 0.1 (#3362) 2023-09-28 15:13:37 +03:00
BarfingLemurs
ffe88a36a9
readme : add some recent perplexity and bpw measurements to READMES, link for k-quants (#3340)
* Update README.md

* Update README.md

* Update README.md with k-quants bpw measurements
2023-09-27 18:30:36 +03:00
2f38b454
1726f9626f
docs: Fix typo CLBlast_DIR var. (#3330) 2023-09-25 20:24:52 +02:00
Lee Drake
bc9d3e3971
Update README.md (#3289)
* Update README.md

* Update README.md

Co-authored-by: slaren <slarengh@gmail.com>

---------

Co-authored-by: slaren <slarengh@gmail.com>
2023-09-21 21:00:24 +02:00
Georgi Gerganov
7eb41179ed
readme : update hot topics 2023-09-20 20:48:22 +03:00
Johannes Gäßler
111163e246
CUDA: enable peer access between devices (#2470) 2023-09-17 16:37:53 +02:00
dylan
980ab41afb
docker : add gpu image CI builds (#3103)
Enables the GPU enabled container images to be built and pushed
alongside the CPU containers.

Co-authored-by: canardleteer <eris.has.a.dad+github@gmail.com>
2023-09-14 19:47:00 +03:00
Ikko Eltociear Ashimine
7d99aca759
readme : fix typo (#3043)
* readme : fix typo

acceleation -> acceleration

* Update README.md

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-09-08 19:04:32 +03:00
Georgi Gerganov
94f10b91ed
readme : update hot tpoics 2023-09-08 18:18:04 +03:00
Yui
6ff712a6d1
Update deprecated GGML TheBloke links to GGUF (#3079) 2023-09-08 12:32:55 +02:00
Georgi Gerganov
e36ecdccc8
build : on Mac OS enable Metal by default (#2901)
* build : on Mac OS enable Metal by default

* make : try to fix build on Linux

* make : move targets back to the top

* make : fix target clean

* llama : enable GPU inference by default with Metal

* llama : fix vocab_only logic when GPU is enabled

* common : better `n_gpu_layers` assignment

* readme : update Metal instructions

* make : fix merge conflict remnants

* gitignore : metal
2023-09-04 22:26:24 +03:00
Ido S
340af42f09
docs : add catai to README.md (#2967) 2023-09-03 08:50:51 +03:00
bandoti
52315a4216
readme : update clblast instructions (#2903)
* Update Windows CLBlast instructions

* Update Windows CLBlast instructions

* Remove trailing whitespace
2023-09-02 15:53:18 +03:00
Konstantin Herud
49bb9cbe0f
docs : add java-llama.cpp to README.md (#2935) 2023-09-01 16:36:14 +03:00
Gilad S
35092fb547
docs : add node-llama-cpp to README.md (#2885) 2023-08-30 11:40:12 +03:00
slaren
c03a243abf
remove outdated references to -eps and -gqa from README (#2881) 2023-08-29 23:17:34 +02:00
Jhen-Jie Hong
74e0caeb82
readme : add react-native binding (#2869) 2023-08-29 12:30:10 +03:00
Georgi Gerganov
da7455d046
readme : fix headings 2023-08-27 15:52:34 +03:00
Georgi Gerganov
c48c5bb0b0
readme : update hot topics 2023-08-27 14:44:35 +03:00
Henri Vasserman
6bbc598a63
ROCm Port (#1087)
* use hipblas based on cublas
* Update Makefile for the Cuda kernels
* Expand arch list and make it overrideable
* Fix multi GPU on multiple amd architectures with rocblas_initialize() (#5)
* add hipBLAS to README
* new build arg LLAMA_CUDA_MMQ_Y
* fix half2 decomposition
* Add intrinsics polyfills for AMD
* AMD assembly optimized __dp4a
* Allow overriding CC_TURING
* use "ROCm" instead of "CUDA"
* ignore all build dirs
* Add Dockerfiles
* fix llama-bench
* fix -nommq help for non CUDA/HIP

---------

Co-authored-by: YellowRoseCx <80486540+YellowRoseCx@users.noreply.github.com>
Co-authored-by: ardfork <134447697+ardfork@users.noreply.github.com>
Co-authored-by: funnbot <22226942+funnbot@users.noreply.github.com>
Co-authored-by: Engininja2 <139037756+Engininja2@users.noreply.github.com>
Co-authored-by: Kerfuffle <44031344+KerfuffleV2@users.noreply.github.com>
Co-authored-by: jammm <2500920+jammm@users.noreply.github.com>
Co-authored-by: jdecourval <7315817+jdecourval@users.noreply.github.com>
2023-08-25 12:09:42 +03:00
Georgi Gerganov
44d5462b5c
readme : fix link 2023-08-23 23:44:19 +03:00
Georgi Gerganov
c7868b0753
minor : fix trailing whitespace 2023-08-23 23:43:00 +03:00
Georgi Gerganov
79da24b58c
readme : update hot topics 2023-08-23 23:41:16 +03:00
Evan Jones
f5fe98d11b
docs : add grammar docs (#2701)
* docs : add grammar docs

* tweaks to grammar guide

* rework GBNF example to be a commented grammar
2023-08-22 21:01:57 -04:00
Georgi Gerganov
6381d4e110
gguf : new file format with flexible meta data (beta) (#2398)
* gguf : first API pass

* gguf : read header + meta data

* gguf : read tensor info

* gguf : initial model loading - not tested

* gguf : add gguf_get_tensor_name()

* gguf : do not support passing existing ggml_context to gguf_init

* gguf : simplify gguf_get_val

* gguf : gguf.c is now part of ggml.c

* gguf : read / write sample models

* gguf : add comments

* refactor : reduce code duplication and better API (#2415)

* gguf : expose the gguf_type enum through the API for now

* gguf : add array support

* gguf.py : some code style changes

* convert.py : start a new simplified implementation by removing old stuff

* convert.py : remove GGML vocab + other obsolete stuff

* GGUF : write tensor (#2426)

* WIP: Write tensor

* GGUF : Support writing tensors in Python

* refactor : rm unused import and upd todos

* fix : fix errors upd writing example

* rm example.gguf

* gitignore *.gguf

* undo formatting

* gguf : add gguf_find_key (#2438)

* gguf.cpp : find key example

* ggml.h : add gguf_find_key

* ggml.c : add gguf_find_key

* gguf : fix writing tensors

* gguf : do not hardcode tensor names to read

* gguf : write sample tensors to read

* gguf : add tokenization constants

* quick and dirty conversion example

* gguf : fix writing gguf arrays

* gguf : write tensors one by one and code reuse

* gguf : fix writing gguf arrays

* gguf : write tensors one by one

* gguf : write tensors one by one

* gguf : write tokenizer data

* gguf : upd gguf conversion script

* Update convert-llama-h5-to-gguf.py

* gguf : handle already encoded string

* ggml.h : get array str and f32

* ggml.c : get arr str and f32

* gguf.py : support any type

* Update convert-llama-h5-to-gguf.py

* gguf : fix set is not subscriptable

* gguf : update convert-llama-h5-to-gguf.py

* constants.py : add layer norm eps

* gguf.py : add layer norm eps and merges

* ggml.h : increase GGML_MAX_NAME to 64

* ggml.c : add gguf_get_arr_n

* Update convert-llama-h5-to-gguf.py

* add gptneox gguf example

* Makefile : add gptneox gguf example

* Update convert-llama-h5-to-gguf.py

* add gptneox gguf example

* Update convert-llama-h5-to-gguf.py

* Update convert-gptneox-h5-to-gguf.py

* Update convert-gptneox-h5-to-gguf.py

* Update convert-llama-h5-to-gguf.py

* gguf : support custom alignment value

* gguf : fix typo in function call

* gguf : mmap tensor data example

* fix : update convert-llama-h5-to-gguf.py

* Update convert-llama-h5-to-gguf.py

* convert-gptneox-h5-to-gguf.py : Special tokens

* gptneox-main.cpp : special tokens

* Update gptneox-main.cpp

* constants.py : special tokens

* gguf.py : accumulate kv and tensor info data + special tokens

* convert-gptneox-h5-to-gguf.py : accumulate kv and ti + special tokens

* gguf : gguf counterpart of llama-util.h

* gguf-util.h : update note

* convert-llama-h5-to-gguf.py : accumulate kv / ti + special tokens

* convert-llama-h5-to-gguf.py : special tokens

* Delete gptneox-common.cpp

* Delete gptneox-common.h

* convert-gptneox-h5-to-gguf.py : gpt2bpe tokenizer

* gptneox-main.cpp : gpt2 bpe tokenizer

* gpt2 bpe tokenizer (handles merges and unicode)

* Makefile : remove gptneox-common

* gguf.py : bytesarray for gpt2bpe tokenizer

* cmpnct_gpt2bpe.hpp : comments

* gguf.py : use custom alignment if present

* gguf : minor stuff

* Update gptneox-main.cpp

* map tensor names

* convert-gptneox-h5-to-gguf.py : map tensor names

* convert-llama-h5-to-gguf.py : map tensor names

* gptneox-main.cpp : map tensor names

* gguf : start implementing libllama in GGUF (WIP)

* gguf : start implementing libllama in GGUF (WIP)

* rm binary commited by mistake

* upd .gitignore

* gguf : calculate n_mult

* gguf :  inference with 7B model working (WIP)

* gguf : rm deprecated function

* gguf : start implementing gguf_file_saver (WIP)

* gguf : start implementing gguf_file_saver (WIP)

* gguf : start implementing gguf_file_saver (WIP)

* gguf : add gguf_get_kv_type

* gguf : add gguf_get_kv_type

* gguf : write metadata in gguf_file_saver (WIP)

* gguf : write metadata in gguf_file_saver (WIP)

* gguf : write metadata in gguf_file_saver

* gguf : rm references to old file formats

* gguf : shorter name for member variable

* gguf : rm redundant method

* gguf : get rid of n_mult, read n_ff from file

* Update gguf_tensor_map.py

* Update gptneox-main.cpp

* gguf : rm references to old file magics

* gguf : start implementing quantization (WIP)

* gguf : start implementing quantization (WIP)

* gguf : start implementing quantization (WIP)

* gguf : start implementing quantization (WIP)

* gguf : start implementing quantization (WIP)

* gguf : start implementing quantization (WIP)

* gguf : quantization is working

* gguf : roper closing of file

* gguf.py : no need to convert tensors twice

* convert-gptneox-h5-to-gguf.py : no need to convert tensors twice

* convert-llama-h5-to-gguf.py : no need to convert tensors twice

* convert-gptneox-h5-to-gguf.py : simplify nbytes

* convert-llama-h5-to-gguf.py : simplify nbytes

* gptneox-main.cpp : n_layer --> n_block

* constants.py : n_layer --> n_block

* gguf.py : n_layer --> n_block

* convert-gptneox-h5-to-gguf.py : n_layer --> n_block

* convert-llama-h5-to-gguf.py : n_layer --> n_block

* gptneox-main.cpp : n_layer --> n_block

* Update gguf_tensor_map.py

* convert-gptneox-h5-to-gguf.py : load model in parts to save memory

* convert-llama-h5-to-gguf.py : load model in parts to save memory

* convert : write more metadata for LLaMA

* convert : rm quantization version

* convert-gptneox-h5-to-gguf.py : add file_type key

* gptneox-main.cpp : add file_type key

* fix conflicts

* gguf : add todos and comments

* convert-gptneox-h5-to-gguf.py : tensor name map changes

* Create gguf_namemap.py : tensor name map changes

* Delete gguf_tensor_map.py

* gptneox-main.cpp : tensor name map changes

* convert-llama-h5-to-gguf.py : fixes

* gguf.py : dont add empty strings

* simple : minor style changes

* gguf : use UNIX line ending

* Create convert-llama-7b-pth-to-gguf.py

* llama : sync gguf-llama.cpp with latest llama.cpp (#2608)

* llama : sync gguf-llama.cpp with latest llama.cpp

* minor : indentation + assert

* llama : refactor gguf_buffer and gguf_ctx_buffer

* llama : minor

* gitignore : add gptneox-main

* llama : tokenizer fixes (#2549)

* Merge tokenizer fixes into the gguf branch.

* Add test vocabularies

* convert : update convert-new.py with tokenizer fixes (#2614)

* Merge tokenizer fixes into the gguf branch.

* Add test vocabularies

* Adapt convert-new.py (and fix a clang-cl compiler error on windows)

* llama : sync gguf-llama with llama (#2613)

* llama : sync gguf-llama with llama

* tests : fix build + warnings (test-tokenizer-1 still fails)

* tests : fix wstring_convert

* convert : fix layer names

* llama : sync gguf-llama.cpp

* convert : update HF converter to new tokenizer voodoo magics

* llama : update tokenizer style

* convert-llama-h5-to-gguf.py : add token types

* constants.py : add token types

* gguf.py : add token types

* convert-llama-7b-pth-to-gguf.py : add token types

* gguf-llama.cpp :  fix n_head_kv

* convert-llama-h5-to-gguf.py : add 70b gqa support

* gguf.py : add tensor data layout

* convert-llama-h5-to-gguf.py : add tensor data layout

* convert-llama-7b-pth-to-gguf.py : add tensor data layout

* gptneox-main.cpp : add tensor data layout

* convert-llama-h5-to-gguf.py : clarify the reverse permute

* llama : refactor model loading code (#2620)

* llama : style formatting + remove helper methods

* llama : fix quantization using gguf tool

* llama : simplify gguf_file_saver

* llama : fix method names

* llama : simplify write_header()

* llama : no need to pass full file loader to the file saver

just gguf_ctx

* llama : gguf_file_saver write I32

* llama : refactor tensor names (#2622)

* gguf: update tensor names searched in quantization

* gguf : define tensor names as constants

* gguf : initial write API (not tested yet)

* gguf : write to file API (not tested)

* gguf : initial write API ready + example

* gguf : fix header write

* gguf : fixes + simplify example + add ggml_nbytes_pad()

* gguf : minor

* llama : replace gguf_file_saver with new gguf write API

* gguf : streaming support when writing files

* gguf : remove oboslete write methods

* gguf : remove obosolete gguf_get_arr_xxx API

* llama : simplify gguf_file_loader

* llama : move hparams and vocab from gguf_file_loader to llama_model_loader

* llama : merge gguf-util.h in llama.cpp

* llama : reorder definitions in .cpp to match .h

* llama : minor simplifications

* llama : refactor llama_model_loader (WIP)

wip : remove ggml_ctx from llama_model_loader

wip : merge gguf_file_loader in llama_model_loader

* llama : fix shape prints

* llama : fix Windows build + fix norm_rms_eps key

* llama : throw error on missing KV paris in model meta data

* llama : improve printing + log meta data

* llama : switch print order of meta data

---------

Co-authored-by: M. Yusuf Sarıgöz <yusufsarigoz@gmail.com>

* gguf : deduplicate (#2629)

* gguf : better type names

* dedup : CPU + Metal is working

* ggml : fix warnings about unused results

* llama.cpp : fix line feed and compiler warning

* llama : fix strncpy warning + note token_to_str does not write null

* llama : restore the original load/save session implementation

Will migrate this to GGUF in the future

* convert-llama-h5-to-gguf.py : support alt ctx param name

* ggml : assert when using ggml_mul with non-F32 src1

* examples : dedup simple

---------

Co-authored-by: klosax <131523366+klosax@users.noreply.github.com>

* gguf.py : merge all files in gguf.py

* convert-new.py : pick #2427 for HF 70B support

* examples/gguf : no need to keep q option for quantization any more

* llama.cpp : print actual model size

* llama.cpp : use ggml_elements()

* convert-new.py : output gguf (#2635)

* convert-new.py : output gguf (WIP)

* convert-new.py : add gguf key-value pairs

* llama : add hparams.ctx_train + no longer print ftype

* convert-new.py : minor fixes

* convert-new.py : vocab-only option should work now

* llama : fix tokenizer to use llama_char_to_byte

* tests : add new ggml-vocab-llama.gguf

* convert-new.py : tensor name mapping

* convert-new.py : add map for skipping tensor serialization

* convert-new.py : convert script now works

* gguf.py : pick some of the refactoring from #2644

* convert-new.py : minor fixes

* convert.py : update to support GGUF output

* Revert "ci : disable CI temporary to not waste energy"

This reverts commit 7e82d25f40.

* convert.py : n_head_kv optional and .gguf file extension

* convert.py : better always have n_head_kv and default it to n_head

* llama : sync with recent PRs on master

* editorconfig : ignore models folder

ggml-ci

* ci : update ".bin" to ".gguf" extension

ggml-ci

* llama : fix llama_model_loader memory leak

* gptneox : move as a WIP example

* llama : fix lambda capture

ggml-ci

* ggml : fix bug in gguf_set_kv

ggml-ci

* common.h : .bin --> .gguf

* quantize-stats.cpp : .bin --> .gguf

* convert.py : fix HF tensor permuting / unpacking

ggml-ci

* llama.cpp : typo

* llama : throw error if gguf fails to init from file

ggml-ci

* llama : fix tensor name grepping during quantization

ggml-ci

* gguf.py : write tensors in a single pass (#2644)

* gguf : single pass for writing tensors + refactoring writer

* gguf : single pass for writing tensors + refactoring writer

* gguf : single pass for writing tensors + refactoring writer

* gguf : style fixes in simple conversion script

* gguf : refactor gptneox conversion script

* gguf : rename h5 to hf (for HuggingFace)

* gguf : refactor pth to gguf conversion script

* gguf : rm file_type key and method

* gguf.py : fix vertical alignment

* gguf.py : indentation

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* convert-gptneox-hf-to-gguf.py : fixes

* gguf.py : gptneox mapping

* convert-llama-hf-to-gguf.py : fixes

* convert-llama-7b-pth-to-gguf.py : fixes

* ggml.h : reverse GGUF_MAGIC

* gguf.py : reverse GGUF_MAGIC

* test-tokenizer-0.cpp : fix warning

* llama.cpp : print kv general.name

* llama.cpp : get special token kv and linefeed token id

* llama : print number of tensors per type + print arch + style

* tests : update vocab file with new magic

* editorconfig : fix whitespaces

* llama : re-order functions

* llama : remove C++ API + reorganize common source in /common dir

* llama : minor API updates

* llama : avoid hardcoded special tokens

* llama : fix MPI build

ggml-ci

* llama : introduce enum llama_vocab_type + remove hardcoded string constants

* convert-falcon-hf-to-gguf.py : falcon HF --> gguf conversion, not tested

* falcon-main.cpp : falcon inference example

* convert-falcon-hf-to-gguf.py : remove extra kv

* convert-gptneox-hf-to-gguf.py : remove extra kv

* convert-llama-7b-pth-to-gguf.py : remove extra kv

* convert-llama-hf-to-gguf.py : remove extra kv

* gguf.py : fix for falcon 40b

* falcon-main.cpp : fix for falcon 40b

* convert-falcon-hf-to-gguf.py : update ref

* convert-falcon-hf-to-gguf.py : add tensor data layout

* cmpnct_gpt2bpe.hpp : fixes

* falcon-main.cpp : fixes

* gptneox-main.cpp : fixes

* cmpnct_gpt2bpe.hpp : remove non-general stuff

* Update examples/server/README.md

Co-authored-by: slaren <slarengh@gmail.com>

* cmpnct_gpt2bpe.hpp : cleanup

* convert-llama-hf-to-gguf.py : special tokens

* convert-llama-7b-pth-to-gguf.py : special tokens

* convert-permute-debug.py : permute debug print

* convert-permute-debug-master.py : permute debug for master

* convert-permute-debug.py : change permute type of attn_q

* convert.py : 70b model working (change attn_q permute)

* Delete convert-permute-debug-master.py

* Delete convert-permute-debug.py

* convert-llama-hf-to-gguf.py : fix attn_q permute

* gguf.py : fix rope scale kv

* convert-llama-hf-to-gguf.py : rope scale and added tokens

* convert-llama-7b-pth-to-gguf.py : rope scale and added tokens

* llama.cpp : use rope scale kv

* convert-llama-7b-pth-to-gguf.py : rope scale fix

* convert-llama-hf-to-gguf.py : rope scale fix

* py : fix whitespace

* gguf : add Python script to convert GGMLv3 LLaMA models to GGUF (#2682)

* First pass at converting GGMLv3 LLaMA models to GGUF

* Cleanups, better output during conversion

* Fix vocab space conversion logic

* More vocab conversion fixes

* Add description to converted GGUF files

* Improve help text, expand warning

* Allow specifying name and description for output GGUF

* Allow overriding vocab and hyperparams from original model metadata

* Use correct params override var name

* Fix wrong type size for Q8_K

Better handling of original style metadata

* Set default value for gguf add_tensor raw_shape KW arg

* llama : improve token type support (#2668)

* Merge tokenizer fixes into the gguf branch.

* Add test vocabularies

* Adapt convert-new.py (and fix a clang-cl compiler error on windows)

* Improved tokenizer test

But does it work on MacOS?

* Improve token type support

- Added @klosax code to convert.py
- Improved token type support in vocabulary

* Exclude platform dependent tests

* More sentencepiece compatibility by eliminating magic numbers

* Restored accidentally removed comment

* llama : add API for token type

ggml-ci

* tests : use new tokenizer type API (#2692)

* Merge tokenizer fixes into the gguf branch.

* Add test vocabularies

* Adapt convert-new.py (and fix a clang-cl compiler error on windows)

* Improved tokenizer test

But does it work on MacOS?

* Improve token type support

- Added @klosax code to convert.py
- Improved token type support in vocabulary

* Exclude platform dependent tests

* More sentencepiece compatibility by eliminating magic numbers

* Restored accidentally removed comment

* Improve commentary

* Use token type API in test-tokenizer-1.cpp

* py : cosmetics

* readme : add notice about new file format

ggml-ci

---------

Co-authored-by: M. Yusuf Sarıgöz <yusufsarigoz@gmail.com>
Co-authored-by: klosax <131523366+klosax@users.noreply.github.com>
Co-authored-by: goerch <jhr.walter@t-online.de>
Co-authored-by: slaren <slarengh@gmail.com>
Co-authored-by: Kerfuffle <44031344+KerfuffleV2@users.noreply.github.com>
2023-08-21 23:07:43 +03:00
Adrian
2d8b76a110
Add link to clojure bindings to Readme. (#2659) 2023-08-18 21:39:22 +02:00
Georgi Gerganov
7af633aec3
readme : incoming BREAKING CHANGE 2023-08-18 17:48:31 +03:00
mdrokz
eaf98c2649
readme : add link to Rust bindings (#2656) 2023-08-18 13:17:58 +03:00
Johannes Gäßler
0992a7b8b1
README: fix LLAMA_CUDA_MMV_Y documentation (#2647) 2023-08-17 23:57:59 +02:00
Henri Vasserman
6ddeefad9b
[Zig] Fixing Zig build and improvements (#2554)
* Fix zig after console.o was split

* Better include and flag management

* Change LTO to option
2023-08-17 23:11:18 +03:00
Johannes Gäßler
25d43e0eb5
CUDA: tuned mul_mat_q kernels (#2546) 2023-08-09 09:42:34 +02:00
ldwang
220d931864
readme : add Aquila-7B model series to supported models (#2487)
* support bpe tokenizer in convert

Signed-off-by: ldwang <ftgreat@gmail.com>

* support bpe tokenizer in convert

Signed-off-by: ldwang <ftgreat@gmail.com>

* support bpe tokenizer in convert, fix

Signed-off-by: ldwang <ftgreat@gmail.com>

* Add Aquila-7B models in README.md

Signed-off-by: ldwang <ftgreat@gmail.com>

* Up Aquila-7B models in README.md

Signed-off-by: ldwang <ftgreat@gmail.com>

---------

Signed-off-by: ldwang <ftgreat@gmail.com>
Co-authored-by: ldwang <ftgreat@gmail.com>
2023-08-02 11:21:11 +03:00
Yiming Cui
a312193e18
readme : Add Chinese LLaMA-2 / Alpaca-2 to supported models (#2475)
* add support for chinese llama-2 / alpaca-2

* remove white spaces
2023-08-02 09:18:31 +03:00
Johannes Gäßler
0728c5a8b9
CUDA: mmq CLI option, fixed mmq build issues (#2453) 2023-07-31 15:44:35 +02:00
Johannes Gäßler
11f3ca06b8
CUDA: Quantized matrix matrix multiplication (#2160)
* mmq implementation for non k-quants

* q6_K

* q2_K

* q3_k

* q4_K

* vdr

* q5_K

* faster q8_1 loading

* loop unrolling

* add __restrict__

* q2_K sc_high

* GGML_CUDA_MMQ_Y

* Updated Makefile

* Update Makefile

* DMMV_F16 -> F16

* Updated README, CMakeLists

* Fix CMakeLists.txt

* Fix CMakeLists.txt

* Fix multi GPU out-of-bounds
2023-07-29 23:04:44 +02:00
niansa/tuxifan
edcc7ae7d2
Obtaining LLaMA 2 instructions (#2308)
* Obtaining LLaMA 2 instructions

* Removed sharing warning for LLaMA 2

* Linked TheBloke's GGML repos

* Add LLaMA 2 to list of supported models

* Added LLaMA 2 usage instructions

* Added links to LLaMA 2 70B models
2023-07-28 03:14:11 +02:00
Johannes Gäßler
70d26ac388
Fix __dp4a documentation (#2348) 2023-07-23 17:49:06 +02:00
Jose Maldonado
91171b8072
make : fix CLBLAST compile support in FreeBSD (#2331)
* Fix Makefile for CLBLAST compile support and instructions for compile llama.cpp FreeBSD

* More general use-case for CLBLAST support (Linux and FreeBSD)
2023-07-23 14:52:08 +03:00
wzy
78a3d13424
flake : remove intel mkl from flake.nix due to missing files (#2277)
NixOS's mkl misses some libraries like mkl-sdl.pc. See #2261
Currently NixOS doesn't have intel C compiler (icx, icpx). See https://discourse.nixos.org/t/packaging-intel-math-kernel-libraries-mkl/975
So remove it from flake.nix

Some minor changes:

- Change pkgs.python310 to pkgs.python3 to keep latest
- Add pkgconfig to devShells.default
- Remove installPhase because we have `cmake --install` from #2256
2023-07-21 13:26:34 +03:00
wzy
45a1b07e9b
flake : update flake.nix (#2270)
When `isx86_32 || isx86_64`, it will use mkl, else openblas

According to
https://discourse.nixos.org/t/rpath-of-binary-contains-a-forbidden-reference-to-build/12200/3,
add -DCMAKE_SKIP_BUILD_RPATH=ON

Fix #2261, Nix doesn't provide mkl-sdl.pc.
When we build with -DBUILD_SHARED_LIBS=ON, -DLLAMA_BLAS_VENDOR=Intel10_lp64
replace mkl-sdl.pc by mkl-dynamic-lp64-iomp.pc
2023-07-19 10:01:55 +03:00
Jiří Podivín
27ab66e437
py : turn verify-checksum-models.py into executable (#2245)
README.md was adjusted to reflect the change.

Signed-off-by: Jiri Podivin <jpodivin@gmail.com>
2023-07-16 22:54:47 +03:00
Chad Brewbaker
917831c63a
readme : fix zig build instructions (#2171) 2023-07-11 19:03:06 +03:00
Evan Miller
5656d10599
mpi : add support for distributed inference via MPI (#2099)
* MPI support, first cut

* fix warnings, update README

* fixes

* wrap includes

* PR comments

* Update CMakeLists.txt

* Add GH workflow, fix test

* Add info to README

* mpi : trying to move more MPI stuff into ggml-mpi (WIP) (#2099)

* mpi : add names for layer inputs + prep ggml_mpi_graph_compute()

* mpi : move all MPI logic into ggml-mpi

Not tested yet

* mpi : various fixes - communication now works but results are wrong

* mpi : fix output tensor after MPI compute (still not working)

* mpi : fix inference

* mpi : minor

* Add OpenMPI to GH action

* [mpi] continue-on-error: true

* mpi : fix after master merge

* [mpi] Link MPI C++ libraries to fix OpenMPI

* tests : fix new llama_backend API

* [mpi] use MPI_INT32_T

* mpi : factor out recv / send in functions and reuse

* mpi : extend API to allow usage with outer backends (e.g. Metal)

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-07-10 18:49:56 +03:00
JackJollimore
18780e0a5e
readme : update Termux instructions (#2147)
The file pathing is significant when running models inside of Termux on Android devices. llama.cpp performance is improved with loading a .bin from the $HOME directory.
2023-07-09 11:20:43 +03:00
rankaiyx
2492a53fd0
readme : add more docs indexes (#2127)
* Update README.md to add more docs indexes

* Update README.md to add more docs indexes
2023-07-09 10:38:42 +03:00
dylan
84525e7962
docker : add support for CUDA in docker (#1461)
Co-authored-by: canardleteer <eris.has.a.dad+github@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-07-07 21:25:25 +03:00
Judd
36680f6e40
convert : update for baichuan (#2081)
1. guess n_layers;
2. relax warnings on context size;
3. add a note that its derivations are also supported.

Co-authored-by: Judd <foldl@boxvest.com>
2023-07-06 19:23:49 +03:00
Johannes Gäßler
924dd22fd3
Quantized dot products for CUDA mul mat vec (#2067) 2023-07-05 14:19:42 +02:00
Georgi Gerganov
b472f3fca5
readme : add link web chat PR 2023-07-04 22:25:22 +03:00
Judd
471aab6e4c
convert : add support of baichuan-7b (#2055)
Co-authored-by: Judd <foldl@boxvest.com>
2023-07-01 20:00:25 +03:00
Roman Parykin
d38e451578
readme : add Scala 3 bindings repo (#2010) 2023-06-26 22:47:59 +03:00
Gustavo Rocha Dias
aa777abbb7
readme : LD_LIBRARY_PATH complement for some Android devices when building with CLBlast inside Termux (#2007)
* docs - Alternative way to build at Android, with CLBlast.

* doc - LD_LIBRARY_PATH complement for some Android devices when building with CLBlast inside Termux.

* doc- fix typo
2023-06-26 22:34:45 +03:00
Georgi Gerganov
412c60e473
readme : add link to new k-quants for visibility 2023-06-26 19:45:09 +03:00
Georgi Gerganov
447ccbe8c3
readme : add new roadmap + manifesto 2023-06-25 16:08:12 +03:00
Georgi Gerganov
66a2555ba6
readme : add Azure CI discussion link 2023-06-25 09:07:03 +03:00
Georgi Gerganov
11da1a85cd
readme : fix whitespaces 2023-06-24 13:38:18 +03:00
Alberto
235b610d65
readme : fixed termux instructions (#1973) 2023-06-24 13:32:13 +03:00
eiery
d7b7484f74
Add OpenLLaMA instructions to the README (#1954)
* add openllama to readme
2023-06-23 10:38:01 +02:00
Rahul Vivek Nair
fb98254f99
Fix typo in README.md (#1961) 2023-06-21 23:48:43 +02:00