Instructions to use sillon/huggingface-tutorial with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sillon/huggingface-tutorial with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="sillon/huggingface-tutorial")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("sillon/huggingface-tutorial") model = AutoModelForQuestionAnswering.from_pretrained("sillon/huggingface-tutorial", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from sillon/huggingface-tutorial: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/sillon/huggingface-tutorial/resolve/20fce9908637705b2aa6f1efd5597cd5d39c4aaa/pytorch_model.bin
- Command line
-
hf download hf://sillon/huggingface-tutorial@20fce9908637705b2aa6f1efd5597cd5d39c4aaa/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sillon/huggingface-tutorial/resolve/20fce9908637705b2aa6f1efd5597cd5d39c4aaa/pytorch_model.bin
431 MB
- Xet hash:
- 9dcce7d79b1b6c701e23bec49fc52db6ffe3665dfd2b4771cc1885d64cf705bf
- Size of remote file:
- 431 MB
- SHA256:
- 033c74f8ccfafc622d44bb73ee67ed454a502c21487ae16db4722d0508ccb4d5
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.