Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

[Fix] Fix llava reproduce error #24

Merged
merged 1 commit into from
Mar 22, 2024
Merged
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension


Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
61 changes: 30 additions & 31 deletions llava_repr_requirements.txt
Original file line number Diff line number Diff line change
@@ -1,33 +1,32 @@
llava@git+https://github.com/haotian-liu/LLaVA@v1.1.3
accelerate>=0.21.0
black==24.1.0
accelerate==0.21.0
datasets==2.16.1
evaluate>=0.4.0
jsonlines
numexpr
peft>=0.2.0
pybind11>=2.6.2
pytablewriter
rouge-score>=0.0.4
sacrebleu>=1.5.0
scikit-learn>=0.24.1
sqlitedict
evaluate==0.4.1
hf_transfer==0.1.6
Jinja2==3.1.3
numpy==1.26.4
openai==1.13.3
packaging==23.2
pandas==2.2.1
Pillow==10.2.0
protobuf==4.25.3
pycocoevalcap==1.2
pycocotools==2.0.7
pytablewriter==1.2.0
pytest==8.0.2
python_Levenshtein==0.25.0
pytz==2024.1
PyYAML==6.0.1
PyYAML==6.0.1
Requests==2.31.0
sacrebleu==2.4.0
scikit_learn==1.2.2
sentencepiece==0.1.99
setuptools==68.2.2
sglang==0.1.12
shortuuid==1.0.12
sqlitedict==2.1.0
tenacity==8.2.3
torch==2.0.1
openai>=1.0.0
pycocoevalcap
tqdm-multiprocess
transformers>=4.36.2
zstandard
pillow
pyyaml
sympy
mpmath
Jinja2
openpyxl
Levenshtein
hf_transfer
tenacity
wandb>=0.16.0
transformers-stream-generator
tiktoken
pre-commit
tokenizers==0.15.2
tqdm==4.66.2
transformers==4.37.2
6 changes: 5 additions & 1 deletion miscs/repr_scripts.sh
Original file line number Diff line number Diff line change
Expand Up @@ -2,9 +2,13 @@
cd lmms_eval;
pip install --no-deps -U -e .

# install LLaVA without building dependencies
cd LLaVA
pip install --no-deps -U -e .

# install all the requirements that require for reproduce llava results
pip install -r llava_repr_requirements.txt

# Run and exactly reproduce llava_v1.5 results!
# mme as an example
accelerate launch --num_processes=1 -m lmms_eval --model llava --model_args pretrained="liuhaotian/llava-v1.5-7b" --tasks mme --batch_size 1 --log_samples --log_samples_sufix reproduce --output_path ./logs/
accelerate launch --num_processes=1 -m lmms_eval --model llava --model_args pretrained="liuhaotian/llava-v1.5-7b,use_flash_attention_2=False" --tasks mme --batch_size 1 --log_samples --log_samples_sufix reproduce --output_path ./logs/
Loading