Instructions to use Fujitsu/pytorrent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Fujitsu/pytorrent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Fujitsu/pytorrent")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Fujitsu/pytorrent") model = AutoModel.from_pretrained("Fujitsu/pytorrent", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Fujitsu/pytorrent: direct link, hf CLI and curl.
- Browser
- Download file 358 MB
-
https://huggingface.co/Fujitsu/pytorrent/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Fujitsu/pytorrent/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Fujitsu/pytorrent/resolve/main/pytorch_model.bin
358 MB
- Xet hash:
- b77a237372a7b62d3536117ee85c795e5c7f5fead547150ebeab7b4912da9531
- Size of remote file:
- 358 MB
- SHA256:
- d552d02cc6d8b3597eac388e8805500704d8856e9f30305bae6b02ea21df2ae6
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