Instructions to use calisolo/OFA_huge_NICE_captioning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use calisolo/OFA_huge_NICE_captioning with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import OFAModelForCaption model = OFAModelForCaption.from_pretrained("calisolo/OFA_huge_NICE_captioning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download candidate1_trainLess/pytorch_model.bin from calisolo/OFA_huge_NICE_captioning: direct link, hf CLI and curl.
- Browser
- Download file 3.79 GB
-
https://huggingface.co/calisolo/OFA_huge_NICE_captioning/resolve/main/candidate1_trainLess/pytorch_model.bin
- Command line
-
hf download hf://calisolo/OFA_huge_NICE_captioning/candidate1_trainLess/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/calisolo/OFA_huge_NICE_captioning/resolve/main/candidate1_trainLess/pytorch_model.bin
3.79 GB
- Xet hash:
- d761e18de12ab3be2511c6b3d5b66aea0f40fcefbce6dbebb32cb4755a912197
- Size of remote file:
- 3.79 GB
- SHA256:
- a0bb830b18a2245756810d13732f645c138512924eff5862e896e65069178457
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