Commit Graph

14 Commits

Author SHA1 Message Date
ditsuke
01a5f06550 chore: Remove rebase artifacts 2024-07-04 15:39:13 +00:00
ditsuke
07786a61a2 chore: Fixup requirements and build 2024-07-04 15:39:13 +00:00
ditsuke
821922916f fix: Update script paths in CI scripts 2024-07-04 15:39:13 +00:00
Galunid
9c4c9cc83f
Move convert.py to examples/convert-legacy-llama.py (#7430)
* Move convert.py to examples/convert-no-torch.py

* Fix CI, scripts, readme files

* convert-no-torch -> convert-legacy-llama

* Move vocab thing to vocab.py

* Fix convert-no-torch -> convert-legacy-llama

* Fix lost convert.py in ci/run.sh

* Fix imports

* Fix gguf not imported correctly

* Fix flake8 complaints

* Fix check-requirements.sh

* Get rid of ADDED_TOKENS_FILE, FAST_TOKENIZER_FILE

* Review fixes
2024-05-30 21:40:00 +10:00
Georgi Gerganov
fabf30b4c4
llama : remove Persimmon (#7408)
* llama : remove Persimmon

* requirements : remove
2024-05-21 02:35:28 +10:00
slaren
b228aba91a
remove convert-lora-to-ggml.py (#7204) 2024-05-12 02:29:33 +02:00
Georgi Gerganov
f4ab2a4147
llama : fix BPE pre-tokenization (#6920)
* merged the changes from deepseeker models to main branch

* Moved regex patterns to unicode.cpp and updated unicode.h

* Moved header files

* Resolved issues

* added and refactored unicode_regex_split and related functions

* Updated/merged the deepseek coder pr

* Refactored code

* Adding unicode regex mappings

* Adding unicode regex function

* Added needed functionality, testing remains

* Fixed issues

* Fixed issue with gpt2 regex custom preprocessor

* unicode : fix? unicode_wstring_to_utf8

* lint : fix whitespaces

* tests : add tokenizer tests for numbers

* unicode : remove redundant headers

* tests : remove and rename tokenizer test scripts

* tests : add sample usage

* gguf-py : reader prints warnings on duplicate keys

* llama : towards llama3 tokenization support (wip)

* unicode : shot in the dark to fix tests on Windows

* unicode : first try custom implementations

* convert : add "tokenizer.ggml.pre" GGUF KV (wip)

* llama : use new pre-tokenizer type

* convert : fix pre-tokenizer type writing

* lint : fix

* make : add test-tokenizer-0-llama-v3

* wip

* models : add llama v3 vocab file

* llama : adapt punctuation regex + add llama 3 regex

* minor

* unicode : set bomb

* unicode : set bomb

* unicode : always use std::wregex

* unicode : support \p{N}, \p{L} and \p{P} natively

* unicode : try fix windows

* unicode : category support via std::regex

* unicode : clean-up

* unicode : simplify

* convert : add convert-hf-to-gguf-update.py

ggml-ci

* lint : update

* convert : add falcon

ggml-ci

* unicode : normalize signatures

* lint : fix

* lint : fix

* convert : remove unused functions

* convert : add comments

* convert : exercise contractions

ggml-ci

* lint : fix

* cmake : refactor test targets

* tests : refactor vocab tests

ggml-ci

* tests : add more vocabs and tests

ggml-ci

* unicode : cleanup

* scripts : ignore new update script in check-requirements.sh

* models : add phi-3, mpt, gpt-2, starcoder

* tests : disable obsolete

ggml-ci

* tests : use faster bpe test

ggml-ci

* llama : more prominent warning for old BPE models

* tests : disable test-tokenizer-1-bpe due to slowness

ggml-ci

---------

Co-authored-by: Jaggzh <jaggz.h@gmail.com>
Co-authored-by: Kazim Abrar Mahi <kazimabrarmahi135@gmail.com>
2024-04-29 16:58:41 +03:00
crasm
04ac0607e9
python : add check-requirements.sh and GitHub workflow (#4585)
* python: add check-requirements.sh and GitHub workflow

This script and workflow forces package versions to remain compatible
across all convert*.py scripts, while allowing secondary convert scripts
to import dependencies not wanted in convert.py.

* Move requirements into ./requirements

* Fail on "==" being used for package requirements (but can be suppressed)

* Enforce "compatible release" syntax instead of ==

* Update workflow

* Add upper version bound for transformers and protobuf

* improve check-requirements.sh

* small syntax change

* don't remove venvs if nocleanup is passed

* See if this fixes docker workflow

* Move check-requirements.sh into ./scripts/

---------

Co-authored-by: Jared Van Bortel <jared@nomic.ai>
2023-12-29 16:50:29 +02:00
wonjun Jang
c50e400163
py : add protobuf dependency (#4466) 2023-12-14 14:44:49 +02:00
wonjun Jang
873637afc7
convert : support loading vocab from fast tokenizer config (#3633)
* Add HFVocab into convert.py

* Update convert.py

* Update convert.py

* add bytes_to_unicode function

* change add_meta_vocab fucntion

* remove debug code

* remove byte_encoder

* Add newline between classes

* Check tokenizer.json when tokenizer.model is not exist.

* Move transformers dependency to local code

* Add error context with 'raise from'

* Add fast tokenizer option to BpeVocab

* Update convert.py

* Add VocabLoader and remove *Vocab class

* Add transformers dependency

* remove added tokens and check newline token to decide spm or bpe

* Update convert.py

* Add special token type

* Update convert.py

* Update convert.py

* Update convert.py

* Fix typo in convert.py

* Fix when params.n_vocab < tokenizer vocab size

* update vocab class

* change funtion name

* Remove unused variable/functions, add types to class variable and methods, delete blank liens

* fix flake8 warnings

* code style cleanup

* make mypy happy

* change exception

---------

Co-authored-by: Jared Van Bortel <jared@nomic.ai>
2023-12-14 10:09:34 +02:00
Tom C
c47066d833
py : change version of numpy requirement to 1.24.4 (#3515)
Co-authored-by: Lyjia <me@lyjia.us>
2023-10-07 12:56:15 +03:00
M. Yusuf Sarıgöz
87e3733f24
gguf : make gguf pip-installable
* gitignore : add dist and rm pyproject.toml

* gguf: prepare as Pip package

* gguf: prepare as Pip package

* gguf : fix line endings

* requirements : add gguf

* gguf : update readme with build notes

* gguf : update readme with build notes

* gguf : add notes for tests
2023-08-25 09:26:05 +03:00
Pavol Rusnak
489093548c
py : bump sentencepiece to 0.1.98 to support Python 3.11 (#976) 2023-04-14 19:46:49 +00:00
comex
723dac55fa
py : new conversion script (#545)
Current status: Working, except for the latest GPTQ-for-LLaMa format
  that includes `g_idx`.  This turns out to require changes to GGML, so
  for now it only works if you use the `--outtype` option to dequantize it
  back to f16 (which is pointless except for debugging).

  I also included some cleanup for the C++ code.

  This script is meant to replace all the existing conversion scripts
  (including the ones that convert from older GGML formats), while also
  adding support for some new formats.  Specifically, I've tested with:

  - [x] `LLaMA` (original)
  - [x] `llama-65b-4bit`
  - [x] `alpaca-native`
  - [x] `alpaca-native-4bit`
  - [x] LLaMA converted to 'transformers' format using
        `convert_llama_weights_to_hf.py`
  - [x] `alpaca-native` quantized with `--true-sequential --act-order
        --groupsize 128` (dequantized only)
  - [x] same as above plus `--save_safetensors`
  - [x] GPT4All
  - [x] stock unversioned ggml
  - [x] ggmh

  There's enough overlap in the logic needed to handle these different
  cases that it seemed best to move to a single script.

  I haven't tried this with Alpaca-LoRA because I don't know where to find
  it.

  Useful features:

  - Uses multiple threads for a speedup in some cases (though the Python
    GIL limits the gain, and sometimes it's disk-bound anyway).

  - Combines split models into a single file (both the intra-tensor split
    of the original and the inter-tensor split of 'transformers' format
    files).  Single files are more convenient to work with and more
    friendly to future changes to use memory mapping on the C++ side.  To
    accomplish this without increasing memory requirements, it has some
    custom loading code which avoids loading whole input files into memory
    at once.

  - Because of the custom loading code, it no longer depends in PyTorch,
    which might make installing dependencies slightly easier or faster...
    although it still depends on NumPy and sentencepiece, so I don't know
    if there's any meaningful difference.  In any case, I also added a
    requirements.txt file to lock the dependency versions in case of any
    future breaking changes.

  - Type annotations checked with mypy.

  - Some attempts to be extra user-friendly:

      - The script tries to be forgiving with arguments, e.g. you can
        specify either the model file itself or the directory containing
        it.

      - The script doesn't depend on config.json / params.json, just in
        case the user downloaded files individually and doesn't have those
        handy.  But you still need tokenizer.model and, for Alpaca,
        added_tokens.json.

      - The script tries to give a helpful error message if
        added_tokens.json is missing.
2023-04-14 10:03:03 +03:00