Instructions to use facebook/flava-full with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/flava-full with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForPreTraining processor = AutoProcessor.from_pretrained("facebook/flava-full") model = AutoModelForPreTraining.from_pretrained("facebook/flava-full", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from facebook/flava-full: direct link, hf CLI and curl.
- Browser
- Download file 1.43 GB
-
https://huggingface.co/facebook/flava-full/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://facebook/flava-full/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/facebook/flava-full/resolve/main/pytorch_model.bin
1.43 GB
- Xet hash:
- 42e3d5c73afced91037236872ea651263554fafdd01a84d21eb2d38dc1160fd1
- Size of remote file:
- 1.43 GB
- SHA256:
- de8cb370b6412f4b3c5a7d89d563e357004b252225dadea42abe54d484c036e6
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