■ list_pretrained 함수를 사용해 멀티 모달 임베딩 모델 리스트를 조회하는 방법을 보여준다.
▶ main.py
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import open_clip import pandas as pd tupleList = open_clip.list_pretrained() dataFrame = pd.DataFrame(tupleList, columns = ["model_name", "checkpoint"]) print(dataFrame) """ model_name checkpoint 0 RN50 openai 1 RN50 yfcc15m 2 RN50 cc12m 3 RN101 openai 4 RN101 yfcc15m .. ... ... 160 ViT-L-14-336-quickgelu openai 161 ViT-H-14-quickgelu metaclip_fullcc 162 ViT-H-14-quickgelu dfn5b 163 ViT-H-14-378-quickgelu dfn5b 164 ViT-bigG-14-quickgelu metaclip_fullcc """ |
▶ requirements.txt
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certifi==2024.12.14 charset-normalizer==3.4.1 filelock==3.16.1 fsspec==2024.12.0 ftfy==6.3.1 huggingface-hub==0.27.1 idna==3.10 Jinja2==3.1.5 MarkupSafe==3.0.2 mpmath==1.3.0 networkx==3.4.2 numpy==2.2.1 nvidia-cublas-cu12==12.4.5.8 nvidia-cuda-cupti-cu12==12.4.127 nvidia-cuda-nvrtc-cu12==12.4.127 nvidia-cuda-runtime-cu12==12.4.127 nvidia-cudnn-cu12==9.1.0.70 nvidia-cufft-cu12==11.2.1.3 nvidia-curand-cu12==10.3.5.147 nvidia-cusolver-cu12==11.6.1.9 nvidia-cusparse-cu12==12.3.1.170 nvidia-nccl-cu12==2.21.5 nvidia-nvjitlink-cu12==12.4.127 nvidia-nvtx-cu12==12.4.127 open_clip_torch==2.30.0 packaging==24.2 pandas==2.2.3 pillow==11.1.0 python-dateutil==2.9.0.post0 pytz==2024.2 PyYAML==6.0.2 regex==2024.11.6 requests==2.32.3 safetensors==0.5.2 six==1.17.0 sympy==1.13.1 timm==1.0.13 torch==2.5.1 torchvision==0.20.1 tqdm==4.67.1 triton==3.1.0 typing_extensions==4.12.2 tzdata==2024.2 urllib3==2.3.0 wcwidth==0.2.13 |
※ pip install open_clip_torch pandas 명령을 실행했다.