awesome-llama: https://github.com/misonsky/HiFT
chinese-llama chinese-llama-65b huggingface-transformers large-language-models llama2 llama3 lora memory-efficient-tuning peft-fine-tuning-llm pytorch-implementation transformers
Score: 7.171656822768514
Last synced: about 4 hours ago
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Repository metadata:
memory-efficient fine-tuning; support 24G GPU memory fine-tuning 7B
- Host: GitHub
- URL: https://github.com/misonsky/HiFT
- Owner: misonsky
- License: apache-2.0
- Created: 2024-05-01T17:44:44.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2024-05-26T23:41:42.000Z (about 2 years ago)
- Last Synced: 2026-05-31T08:04:10.403Z (20 days ago)
- Topics: chinese-llama, chinese-llama-65b, huggingface-transformers, large-language-models, llama2, llama3, lora, memory-efficient-tuning, peft-fine-tuning-llm, pytorch-implementation, transformers
- Language: Python
- Homepage:
- Size: 41.3 MB
- Stars: 21
- Watchers: 1
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
Owner metadata:
- Name: misonsky
- Login: misonsky
- Email:
- Kind: user
- Description:
- Website:
- Location:
- Twitter:
- Company:
- Icon url: https://avatars.githubusercontent.com/u/77843536?v=4
- Repositories: 8
- Last Synced at: 2024-05-22T00:04:19.967Z
- Profile URL: https://github.com/misonsky
GitHub Events
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- Watch event: 3
- Total: 3
Last Year
- Total: 0
Committers metadata
Last synced: 15 days ago
Total Commits: 51
Total Committers: 2
Avg Commits per committer: 25.5
Development Distribution Score (DDS): 0.49
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 | |
|---|---|---|
| misonsky | 7****y | 26 |
| AnonymityGithub | 1****b | 25 |
Issue and Pull Request metadata
Last synced: 2 months ago
Total issues: 0
Total pull requests: 0
Average time to close issues: N/A
Average time to close pull requests: N/A
Total issue authors: 0
Total pull request authors: 0
Average comments per issue: 0
Average comments per pull request: 0
Merged pull request: 0
Bot issues: 0
Bot pull requests: 0
Past year issues: 0
Past year pull requests: 0
Past year average time to close issues: N/A
Past year average time to close pull requests: N/A
Past year issue authors: 0
Past year pull request authors: 0
Past year average comments per issue: 0
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
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Package metadata
- Total packages: 1
-
Total downloads:
- pypi: 30 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 5
- Total maintainers: 1
pypi.org: hift
PyTorch implementation of 'HiFT: A Hierarchical Full Parameter Fine-Tuning Strategy', a memory-efficient approach to adapt a large pre-trained deep learning model.
- Homepage: https://github.com/misonsky/HiFT
- Documentation: https://hift.readthedocs.io/
- Licenses: MIT License
- Latest release: 0.0.5 (published about 2 years ago)
- Last Synced: 2026-06-04T11:57:24.007Z (15 days ago)
- Versions: 5
- Dependent Packages: 0
- Dependent Repositories: 0
- Downloads: 30 Last month
-
Rankings:
- Dependent packages count: 9.463%
- Average: 35.947%
- Dependent repos count: 62.431%
- Maintainers (1)
Dependencies
- GitPython ==3.1.40
- HiFT ==0.0.1
- Markdown ==3.5.1
- Pillow *
- PySocks *
- PyYAML *
- Pygments ==2.17.2
- SecretStorage ==3.3.3
- Werkzeug ==3.0.1
- absl-py ==2.0.0
- accelerate ==0.25.0
- aiohttp ==3.9.1
- aiosignal ==1.3.1
- annotated-types ==0.6.0
- appdirs ==1.4.4
- async-timeout ==4.0.3
- attrs ==23.1.0
- backports.tarfile ==1.1.1
- cachetools ==5.3.2
- click ==8.1.7
- colorama ==0.4.6
- datasets ==2.16.0
- deepspeed ==0.12.6
- dill ==0.3.7
- docker-pycreds ==0.4.0
- docutils ==0.20.1
- evaluate ==0.4.1
- filelock *
- frozenlist ==1.4.1
- fsspec ==2023.10.0
- gitdb ==4.0.11
- gmpy2 *
- google-auth ==2.25.2
- google-auth-oauthlib ==1.0.0
- grpcio ==1.60.0
- hjson ==3.1.0
- huggingface-hub ==0.20.1
- importlib-metadata ==7.0.1
- importlib_resources ==6.4.0
- jaraco.classes ==3.4.0
- jaraco.context ==5.3.0
- jaraco.functools ==4.0.1
- jeepney ==0.8.0
- jieba ==0.42.1
- joblib ==1.3.2
- keyring ==25.2.0
- lxml ==4.9.4
- markdown-it-py ==3.0.0
- mdurl ==0.1.2
- mkl-fft ==1.3.1
- mkl-service ==2.4.0
- more-itertools ==10.2.0
- multidict ==6.0.4
- multiprocess ==0.70.15
- nh3 ==0.2.17
- ninja ==1.11.1.1
- nltk ==3.8.1
- oauthlib ==3.2.2
- packaging ==23.2
- pandas ==2.0.3
- peft ==0.7.1
- pkginfo ==1.10.0
- portalocker ==2.8.2
- protobuf ==4.25.1
- psutil ==5.9.7
- py-cpuinfo ==9.0.0
- pyOpenSSL *
- pyarrow ==14.0.2
- pyarrow-hotfix ==0.6
- pyasn1 ==0.5.1
- pyasn1-modules ==0.3.0
- pycparser *
- pydantic ==2.5.3
- pydantic_core ==2.14.6
- pynvml ==11.5.0
- pyparsing ==3.1.1
- python-dateutil ==2.8.2
- pytz ==2023.3.post1
- readme_renderer ==43.0
- regex ==2023.12.25
- requests *
- requests-oauthlib ==1.3.1
- requests-toolbelt ==1.0.0
- responses ==0.18.0
- rfc3986 ==2.0.0
- rich ==13.7.0
- rouge ==1.0.1
- rouge-score ==0.1.2
- rsa ==4.9
- sacrebleu ==2.4.0
- safetensors ==0.4.1
- scikit-learn ==1.3.2
- scipy ==1.10.1
- sentencepiece ==0.1.99
- sentry-sdk ==1.39.1
- setproctitle ==1.3.3
- six *
- smmap ==5.0.1
- sympy *
- tabulate ==0.9.0
- tensorboard ==2.14.0
- tensorboard-data-server ==0.7.2
- tensorboardX ==2.6.2.2
- threadpoolctl ==3.2.0
- tokenizers ==0.15.2
- torch ==2.1.1
- torch_geometric ==2.4.0
- torchaudio ==2.1.1
- torchvision ==0.16.1
- tqdm ==4.66.1
- transformers ==4.36.2
- triton ==2.1.0
- twine ==5.0.0
- typing_extensions *
- tzdata ==2023.3
- urllib3 *
- wandb ==0.16.1
- xxhash ==3.4.1
- yarl ==1.9.4
- zipp ==3.17.0