Instructions to use amir36/tutorial with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amir36/tutorial with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="amir36/tutorial")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("amir36/tutorial") model = AutoModelForMaskedLM.from_pretrained("amir36/tutorial", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from amir36/tutorial: direct link, hf CLI and curl.
- Browser
- Download file 443 MB
-
https://huggingface.co/amir36/tutorial/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://amir36/tutorial/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/amir36/tutorial/resolve/main/pytorch_model.bin
443 MB
- Xet hash:
- dbbe59a10c6b305cd43a143d1295f0be50259341bff95eba5eb4b4ba540d7d67
- Size of remote file:
- 443 MB
- SHA256:
- 61d7b68e4fc05232cba9d4fca837d7f69200af7df7eacb028984bc0480c45f1a
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