awesome-llama: https://github.com/ROIM1998/APT
bert efficient-deep-learning llama2 llm llm-finetuning peft peft-fine-tuning-llm pruning roberta t5
Score: 3.8501476017100584
Last synced: about 7 hours ago
JSON representation
Repository metadata:
[ICML'24 Oral] APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference
- Host: GitHub
- URL: https://github.com/ROIM1998/APT
- Owner: ROIM1998
- License: mit
- Created: 2024-01-24T17:48:44.000Z (over 2 years ago)
- Default Branch: master
- Last Pushed: 2024-06-04T16:47:20.000Z (about 2 years ago)
- Last Synced: 2026-01-12T18:21:35.519Z (5 months ago)
- Topics: bert, efficient-deep-learning, llama2, llm, llm-finetuning, peft, peft-fine-tuning-llm, pruning, roberta, t5
- Language: Python
- Homepage:
- Size: 4.08 MB
- Stars: 46
- Watchers: 2
- Forks: 3
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Owner metadata:
- Name: Bowen Zhao
- Login: ROIM1998
- Email:
- Kind: user
- Description:
- Website: roim1998.github.io
- Location: Bellevue, WA, US
- Twitter: BowenROIM
- Company: University of Washington
- Icon url: https://avatars.githubusercontent.com/u/36983540?u=04e58a7a5a9ec9ee835336c6633ec55a1651ba77&v=4
- Repositories: 1
- Last Synced at: 2023-04-29T00:28:19.023Z
- Profile URL: https://github.com/ROIM1998
GitHub Events
Total
- Fork event: 1
- Issue comment event: 1
- Issues event: 1
- Watch event: 16
- Total: 19
Last Year
- Fork event: 1
- Watch event: 12
- Total: 13
Committers metadata
Last synced: 5 months ago
Total Commits: 6
Total Committers: 1
Avg Commits per committer: 6.0
Development Distribution Score (DDS): 0.0
Commits in past year: 0
Committers in past year: 0
Avg Commits per committer in past year: 0.0
Development Distribution Score (DDS) in past year: 0.0
| Name | Commits | |
|---|---|---|
| ROIM1998 | b****8@u****u | 6 |
Issue and Pull Request metadata
Last synced: 10 months ago
Total issues: 6
Total pull requests: 0
Average time to close issues: 12 days
Average time to close pull requests: N/A
Total issue authors: 6
Total pull request authors: 0
Average comments per issue: 2.17
Average comments per pull request: 0
Merged pull request: 0
Bot issues: 0
Bot pull requests: 0
Past year issues: 5
Past year pull requests: 0
Past year average time to close issues: 15 days
Past year average time to close pull requests: N/A
Past year issue authors: 5
Past year pull request authors: 0
Past year average comments per issue: 1.8
Past year average comments per pull request: 0
Past year merged pull request: 0
Past year bot issues: 0
Past year bot pull requests: 0
Top Issue Authors
- JintuZheng (1)
- jsvir (1)
- au-revoir (1)
- ErichVonTang (1)
- Sid-LCL (1)
- digbangbang (1)
Top Pull Request Authors
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Dependencies
- absl-py ==2.1.0
- accelerate ==0.21.0
- aiohttp ==3.9.5
- aiosignal ==1.3.1
- annotated-types ==0.7.0
- anyio ==4.4.0
- async-timeout ==4.0.3
- attrs ==23.2.0
- certifi ==2024.6.2
- charset-normalizer ==3.3.2
- click ==8.1.7
- cmake ==3.29.3
- contourpy ==1.2.1
- cupy-cuda12x ==13.1.0
- cycler ==0.12.1
- datasets ==2.19.2
- deepspeed ==0.14.2
- dill ==0.3.8
- distro ==1.9.0
- exceptiongroup ==1.2.1
- fastrlock ==0.8.2
- filelock ==3.14.0
- fonttools ==4.53.0
- frozenlist ==1.4.1
- fsspec ==2024.3.1
- h11 ==0.14.0
- hjson ==3.1.0
- httpcore ==1.0.5
- httpx ==0.27.0
- huggingface-hub ==0.23.2
- idna ==3.7
- immutabledict ==4.2.0
- importlib-resources ==6.4.0
- install ==1.3.5
- jinja2 ==3.1.4
- joblib ==1.4.2
- kiwisolver ==1.4.5
- lit ==18.1.6
- markupsafe ==2.1.5
- matplotlib ==3.9.0
- mpmath ==1.3.0
- multidict ==6.0.5
- multiprocess ==0.70.16
- networkx ==3.2.1
- ninja ==1.11.1.1
- nltk ==3.8.1
- numpy ==1.26.4
- nvidia-cublas-cu11 ==11.10.3.66
- nvidia-cublas-cu12 ==12.1.3.1
- nvidia-cuda-cupti-cu11 ==11.7.101
- nvidia-cuda-cupti-cu12 ==12.1.105
- nvidia-cuda-nvrtc-cu11 ==11.7.99
- nvidia-cuda-nvrtc-cu12 ==12.1.105
- nvidia-cuda-runtime-cu11 ==11.7.99
- nvidia-cuda-runtime-cu12 ==12.1.105
- nvidia-cudnn-cu11 ==8.5.0.96
- nvidia-cudnn-cu12 ==8.9.2.26
- nvidia-cufft-cu11 ==10.9.0.58
- nvidia-cufft-cu12 ==11.0.2.54
- nvidia-curand-cu11 ==10.2.10.91
- nvidia-curand-cu12 ==10.3.2.106
- nvidia-cusolver-cu11 ==11.4.0.1
- nvidia-cusolver-cu12 ==11.4.5.107
- nvidia-cusparse-cu11 ==11.7.4.91
- nvidia-cusparse-cu12 ==12.1.0.106
- nvidia-nccl-cu11 ==2.14.3
- nvidia-nccl-cu12 ==2.20.5
- nvidia-nvjitlink-cu12 ==12.5.40
- nvidia-nvtx-cu11 ==11.7.91
- nvidia-nvtx-cu12 ==12.1.105
- openai ==0.28.0
- ortools ==9.6.2534
- packaging ==24.0
- pandas ==2.2.2
- pillow ==10.3.0
- protobuf ==5.27.0
- psutil ==5.9.8
- py-cpuinfo ==9.0.0
- pyarrow ==16.1.0
- pyarrow-hotfix ==0.6
- pydantic ==2.7.3
- pydantic-core ==2.18.4
- pynvml ==11.5.0
- pyparsing ==3.1.2
- python-dateutil ==2.9.0.post0
- pytz ==2024.1
- pyyaml ==6.0.1
- regex ==2024.5.15
- requests ==2.32.3
- rouge-score ==0.1.2
- safetensors ==0.4.3
- scikit-learn ==1.5.0
- scipy ==1.13.1
- seaborn ==0.13.2
- six ==1.16.0
- sniffio ==1.3.1
- sympy ==1.12.1
- threadpoolctl ==3.5.0
- tokenizers ==0.13.3
- torch ==2.0.1
- tqdm ==4.66.4
- transformers ==4.33.1
- triton ==2.0.0
- typing-extensions ==4.12.1
- tzdata ==2024.1
- urllib3 ==2.2.1
- xxhash ==3.4.1
- yarl ==1.9.4
- zipp ==3.19.1
- datasets ==2.10.0
- deepspeed ==0.8.0
- matplotlib ==3.7.1
- nltk ==3.8.1
- numpy ==1.24.3
- ortools ==9.6.2534
- pandas ==1.5.2
- rouge-score ==0.1.2
- scikit_learn ==1.1.3
- scipy ==1.10.1
- seaborn ==0.12.2
- torch ==1.10.2
- tqdm ==4.65.0
- transformers ==4.28.1