Commit Graph

2400 Commits

Author SHA1 Message Date
Xuan Son Nguyen
caa106d4e0
Server: format error to json (#5961)
* server: format error to json

* server: do not crash on grammar error

* fix api key test case

* revert limit max n_predict

* small fix

* correct coding style

* update completion.js

* launch_slot_with_task

* update docs

* update_slots

* update webui

* update readme
2024-03-11 10:56:41 +01:00
Michael Podvitskiy
3202361c5b
ggml, ci : Windows ARM runner and build fixes (#5979)
* windows arm ci

* fix `error C2078: too many initializers` with ggml_vld1q_u32 macro for MSVC ARM64

* fix `warning C4146: unary minus operator applied to unsigned type, result still unsigned`

* fix `error C2065: '__fp16': undeclared identifier`
2024-03-11 11:28:51 +02:00
Minsoo Cheong
332bdfd798
server : maintain chat completion id for streaming responses (#5988)
* server: maintain chat completion id for streaming responses

* Update examples/server/utils.hpp

* Update examples/server/utils.hpp

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-03-11 10:09:32 +02:00
Gilad S
ecab1c75de
cmake : fix subdir for LLAMA_METAL_EMBED_LIBRARY (#5985) 2024-03-11 10:00:08 +02:00
Georgi Gerganov
ee35600b90
llama : fix F16/F32 downcast + improve names (#5980) 2024-03-11 09:56:47 +02:00
Kawrakow
be858f6205
Better 1.5 bit quantization (#5971)
* Trying blocvks of 16 for IQ1_S - seems slightly better

* iq1s_blocks16: Adjust scale fudge factor to 1.125

* iq1s_blocks16: going to blocks of 32

with 2048 lattice points, so same bpw.
This is even better than blocks of 16.
Should I try blocks of 64? But to keep the same
bpw, when I go to 4096 lattice points, I need to
remove blocks alltogether and just have superblocks of
256 weights.

* iq1s_blocks16: Use 2*<x^2> as sigma2 in weight adjustment

* iq1s_blocks16: scalar and AVX2 dot products

* iq1s_blocks16: CUDA dot product

* iq1s_blocks16: Metal works, Neon does not

Metal works but TG is dog slow (35 t/s). PP is OKish (493 t/s).
Not seeing the bug in the Neon implementation for now.

* iq1s_blocks16: fixed Neon

* iq1s_blocks16: very slightly faster TG on Metal

Still pathetic at 37 t/s

* iq1s_blocks16: speedup Metal by packing codebook into uint32_t's

* Formatting

* iq1s_blocks16: uint32_t codebook is also better in CUDA

TG-128 is now 204 t/s up from 194 t/s.
PP-512 is 5890 t/s, so significantly better than other quants

* iq1s_blocks16: slightly faster Neon dot product

* iq1s_blocks16: faster AVX2 dot product

* iq1s_blocks16: adjust to ggml-common.h

---------

Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
2024-03-11 07:51:49 +01:00
Abhilash Majumder
ef3ced26a3
[SYCL] Add q3_s and q1_s (#5886)
* Add q3_s and q1_s

* fix compilation

* fix build

* fix build

* fix build

* enable ops

* rm macro

* increase grid space
2024-03-11 10:27:56 +05:30
AidanBeltonS
3814a07392
[SYCL] Add support for SYCL Nvidia target (#5738)
* Add support for nvidia target in CMake

* Update sycl read-me for Nvidia target

* Fix errors
2024-03-11 09:13:57 +08:00
Georgi Gerganov
bb6d00bbf9
metal : move mm_id indices to shared mem (#5982) 2024-03-10 23:12:48 +02:00
Dean
7ab7b733bb
android : fix utf8 decoding error (#5935)
* examples: fix utf8 decoding error

some models have a tokenizer that decodes an id into an incomplete utf8 sequence, need to validate and wait for next token
one example would be: https://huggingface.co/Qwen/Qwen1.5-1.8B-Chat-GGUF/resolve/main/qwen1_5-1_8b-chat-q4_0.gguf and and an example of the token is 18137

* android : minor

---------

Co-authored-by: zhangfuwen <zhangfuwen@foxmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-03-10 22:03:17 +02:00
Georgi Gerganov
d9f65c97c3
readme : update hot topics 2024-03-10 20:58:26 +02:00
Georgi Gerganov
b838b53ad6
sync : ggml 2024-03-10 20:10:46 +02:00
Georgi Gerganov
df4dc3e7cb
ggml : try fix 32-bit arm compat (whisper/1938)
* ggml : try fix 32-bit arm compat

* ggml : fix cont
2024-03-10 20:10:39 +02:00
Georgi Gerganov
bf47a5eefc
ggml : remove __constant__ specifier for CUDA tables (#5940) 2024-03-10 20:09:24 +02:00
Pierrick Hymbert
fa8a809a91
server: ci: windows build and tests (#5968)
* server: ci: windows build and tests

* server: ci: remove tmp push branch

* server: ci: EOF EOL

* Use builti

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

* server: tests: server graceful shutdown, then kill, then hard kill

* server: tests: remove python2 unicode string

* server: tests: remove wrong comment on server starting,  close_fds is always true

* server: tests: server kill, if pid exists

* server: tests: remove dependency to killall

* server: tests: ci windows: pid exists better handling

---------

Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>
2024-03-10 18:17:47 +01:00
DAN™
bcebd7dbf6
llama : add support for GritLM (#5959)
* add gritlm example

* gritlm results match

* tabs to spaces

* comment out debug printing

* rebase to new embed

* gritlm embeddings are back babeee

* add to gitignore

* allow to toggle embedding mode

* Clean-up GritLM sample code.

* Fix types.

* Flush stdout and output ending newline if streaming.

* mostly style fixes; correct KQ_mask comment

* add causal_attn flag to llama_cparams

* gritml : minor

* llama : minor

---------

Co-authored-by: Douglas Hanley <thesecretaryofwar@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-03-10 17:56:30 +02:00
Clint Herron
2960eae847
grammar : verify parsed state (#5950) 2024-03-10 17:17:43 +02:00
Georgi Gerganov
c78541479c
nix: update flake.lock (#5969)
Flake lock file updates:

• Updated input 'nixpkgs':
    'github:NixOS/nixpkgs/1536926ef5621b09bba54035ae2bb6d806d72ac8' (2024-02-29)
  → 'github:NixOS/nixpkgs/9df3e30ce24fd28c7b3e2de0d986769db5d6225d' (2024-03-06)

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
2024-03-10 16:43:08 +02:00
Pierrick Hymbert
621e86b331
server: benchmark: chat/completions scenario and other llm servers comparison (#5941)
* server: bench: Init a bench scenario with K6
See #5827

* server: bench: EOL EOF

* server: bench: PR feedback and improved k6 script configuration

* server: bench: remove llamacpp_completions_tokens_seconds as it include prompt processing time and it's misleading

server: bench: add max_tokens from SERVER_BENCH_MAX_TOKENS

server: bench: increase truncated rate to 80% before failing

* server: bench: fix doc

* server: bench: change gauge custom metrics to trend

* server: bench: change gauge custom metrics to trend
server: bench: add trend custom metrics for total tokens per second average

* server: bench: doc add an option to debug http request

* server: bench: filter dataset too short and too long sequences

* server: bench: allow to filter out conversation in the dataset based on env variable

* server: bench: fix assistant message sent instead of user message

* server: bench: fix assistant message sent instead of user message

* server : add defrag thold parameter

* server: bench: select prompts based on the current iteration id not randomly to make the bench more reproducible

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-03-09 23:41:49 +01:00
Georgi Gerganov
77d1ac7e00
server : print chat template info 2024-03-09 22:04:00 +02:00
slaren
d894f352bf
perplexity : support using multiple sequences to allow larger batch sizes (#5946)
* perplexity : support using multiple sequences to allow larger batch sizes

ggml-ci

* set cparams.n_parallel to the number of sequences

* print tested n_ctx, add assert
2024-03-09 19:55:54 +01:00
Georgi Gerganov
098dbaab44
readme : update hot topics 2024-03-09 18:14:13 +02:00
Georgi Gerganov
8380ecfb21
ggml : fix unnecessary f32 -> f16 -> f32 casts (mmla) (#5951) 2024-03-09 17:36:20 +02:00
Georgi Gerganov
58308a0ecc
server : fix metrics init (#5964) 2024-03-09 17:34:15 +02:00
Georgi Gerganov
5b09797321
ggml : remove old quantization functions (#5942)
* ggml : remove old quantization functions

ggml-ci

* ggml : simplify ggml_quantize_chunk

ggml-ci

* ggml : restrict correctness

ggml-ci

* ggml : remove hist data from the quantization API

ggml-ci

* tests : remove hist usage in test-backend-ops

ggml-ci

* vulkan : remove hist and fix typo
2024-03-09 15:53:59 +02:00
Georgi Gerganov
97c09585d6
server : clarify some items in the readme (#5957)
* server : clarify some items in the readme

* server : fix typo
2024-03-09 15:47:47 +02:00
SeungWon Jeong
fb215c3832
server : normalize embeddings (#5956)
* output normalize embedding in '/v1/embeddings'

* common : reuse llama_embd_normalize

* common : better normalize impl

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-03-09 14:27:58 +02:00
Georgi Gerganov
2c4f566c88
tests : gitignore ggml-common.h 2024-03-09 14:17:11 +02:00
Alexey Parfenov
0db32beaf0
server : fix passing prompt as tokens (#5955)
* server: fix passing prompt as tokens

* Update examples/server/server.cpp

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-03-09 13:16:53 +02:00
Georgi Gerganov
8a3012a4ad
ggml : add ggml-common.h to deduplicate shared code (#5940)
* ggml : add ggml-common.h to shared code

ggml-ci

* scripts : update sync scripts

* sycl : reuse quantum tables

ggml-ci

* ggml : minor

* ggml : minor

* sycl : try to fix build
2024-03-09 12:47:57 +02:00
Georgi Gerganov
9674aaf35c
server : simplify logic for empty prompts (#5953) 2024-03-09 12:34:18 +02:00
Xuan Son Nguyen
950ba1ab84
Server: reorganize some http logic (#5939)
* refactor static file handler

* use set_pre_routing_handler for validate_api_key

* merge embedding handlers

* correct http verb for endpoints

* fix embedding response

* fix test case CORS Options

* fix code style
2024-03-09 11:27:53 +01:00
Gabe Goodhart
e1fa9569ba
server : add SSL support (#5926)
* add cmake build toggle to enable ssl support in server

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* add flags for ssl key/cert files and use SSLServer if set

All SSL setup is hidden behind CPPHTTPLIB_OPENSSL_SUPPORT in the same
way that the base httlib hides the SSL support

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* Update readme for SSL support in server

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

* Add LLAMA_SERVER_SSL variable setup to top-level Makefile

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>

---------

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
2024-03-09 11:57:09 +02:00
Pierrick Hymbert
fd72d2d2a5
server: tests: add truncated prompt tests, better kv cache size (#5933)
* server: tests: add truncated prompt tests, better size

* server, tests : update regex

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-03-09 11:30:04 +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
compilade
515f7d0d4f
llama : fix quantization of shared token_embd (#5944) 2024-03-08 17:53:37 +02:00
Pierrick Hymbert
76e868821a
server: metrics: add llamacpp:prompt_seconds_total and llamacpp:tokens_predicted_seconds_total, reset bucket only on /metrics. Fix values cast to int. Add Process-Start-Time-Unix header. (#5937)
Closes #5850
2024-03-08 12:25:04 +01:00
Don Mahurin
e457fb3540
llama : assume tied weights if lm_head/output weights is missing (#5824)
This is to support model configurations with "tie_word_embeddings" set to true.

Co-authored-by: Don Mahurin <2797413+dmahurin@users.noreply.github.com>
2024-03-08 12:41:50 +02:00
Georgi Gerganov
af37fd8b30
server : fix EOS token detection with disabled cache (#5938) 2024-03-08 12:40:02 +02:00
UEXTM.com
581ed5c4fe
log : fix MSVC compile errors (#5643)
MSVC gives the following error with the existing macros:
`Error C2059 : syntax error: ','`

This patch adds `##` as a prefix to `__VA_ARGS__` to address this error.
2024-03-08 11:35:04 +02:00
Georgi Gerganov
6cdabe6526
llama-bench : add embeddings option (#5924)
* llama-bench : add embeddings option

* llama-bench : do not hard code embd default value

---------

Co-authored-by: slaren <slarengh@gmail.com>
2024-03-07 16:32:38 +02:00
Neo Zhang Jianyu
89fb735fcf
Revert "[SYCL] fix error when set main gpu to non-zero (#5901)" (#5918)
This reverts commit ceca1aef07.
2024-03-07 12:14:49 +01:00
Minsoo Cheong
55a2a900ff
server : add /v1/completions endpoint (#5914)
* add-`/v1/completions`-endpoint

* add legacy comment to `/completion` endpoint
2024-03-07 12:42:39 +02:00
Georgi Gerganov
2002bc96bf
server : refactor (#5882)
* server : refactoring (wip)

* server : remove llava/clip objects from build

* server : fix empty prompt handling + all slots idle logic

* server : normalize id vars

* server : code style

* server : simplify model chat template validation

* server : code style

* server : minor

* llama : llama_chat_apply_template support null buf

* server : do not process embedding requests when disabled

* server : reorganize structs and enums + naming fixes

* server : merge oai.hpp in utils.hpp

* server : refactor system prompt update at start

* server : disable cached prompts with self-extend

* server : do not process more than n_batch tokens per iter

* server: tests: embeddings use a real embeddings model (#5908)

* server, tests : bump batch to fit 1 embedding prompt

* server: tests: embeddings fix build type Debug is randomly failing (#5911)

* server: tests: embeddings, use different KV Cache size

* server: tests: embeddings, fixed prompt do not exceed n_batch, increase embedding timeout, reduce number of concurrent embeddings

* server: tests: embeddings, no need to wait for server idle as it can timout

* server: refactor: clean up http code (#5912)

* server : avoid n_available var

ggml-ci

* server: refactor: better http codes

* server : simplify json parsing + add comment about t_last

* server : rename server structs

* server : allow to override FQDN in tests

ggml-ci

* server : add comments

---------

Co-authored-by: Pierrick Hymbert <pierrick.hymbert@gmail.com>
2024-03-07 11:41:53 +02:00
Neo Zhang Jianyu
ceca1aef07
[SYCL] fix error when set main gpu to non-zero (#5901)
* fix error when set main gpu to non-zero

* fix delete condition
2024-03-07 16:34:31 +08:00
Jared Van Bortel
e04e04f8fa
ggml : use SYS_get_cpu if SYS_getcpu is not defined (#5906)
Fixes #5694
Fixes ggerganov/whisper.cpp#1894
2024-03-06 15:42:23 -05:00
bobqianic
e25fb4b18f
ggml : use uint8x16_t return type for ggml_vqtbl1q_u8 (#5894)
* use uint8x16_t

* Update ggml-quants.c
2024-03-06 09:35:07 +02:00
Georgi Gerganov
1e35d619a6
convert : remove AWQ remnants (#5768) 2024-03-06 09:13:42 +02:00
Neo Zhang Jianyu
8ced9f7e32
add wait() to make code stable (#5895) 2024-03-06 12:08:32 +08:00
slaren
652ca2bded
compare-llama-bench.py : remove mul_mat_q (#5892) 2024-03-05 22:27:29 +01:00