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/training_args.bin from calisolo/OFA_huge_NICE_captioning: direct link, hf CLI and curl.
- Browser
- Download file 3.32 kB
-
https://huggingface.co/calisolo/OFA_huge_NICE_captioning/resolve/main/candidate1_trainLess/training_args.bin
- Command line
-
hf download hf://calisolo/OFA_huge_NICE_captioning/candidate1_trainLess/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/calisolo/OFA_huge_NICE_captioning/resolve/main/candidate1_trainLess/training_args.bin
3.32 kB
- Xet hash:
- 521807c954c3b0b6cab596504dbd9a26bc42e4219a65bef8693cd92cdabbf83e
- Size of remote file:
- 3.32 kB
- SHA256:
- aef4da31986be3bb58055a93adcca4d9c1a53a688bf4dbe78583eca0d4749451
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