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")# 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 flax_model.msgpack from Fujitsu/pytorrent: direct link, hf CLI and curl.
- Browser
- Download file 358 MB
-
https://huggingface.co/Fujitsu/pytorrent/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://Fujitsu/pytorrent/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/Fujitsu/pytorrent/resolve/main/flax_model.msgpack
358 MB
- Xet hash:
- 9ec545ead6e57c44b0db2c4c1c30171fc99b52d5a792175bc473f069b9883d3e
- Size of remote file:
- 358 MB
- SHA256:
- e0e1cf8e7da24811f5fb1aa3b92d34c09136d800edc5464fbd210eadf5142fc1
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