Instructions to use jmilic/model_name with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jmilic/model_name with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("jmilic/model_name") model = AutoModel.from_pretrained("jmilic/model_name", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from jmilic/model_name: direct link, hf CLI and curl.
- Browser
- Download file 505 MB
-
https://huggingface.co/jmilic/model_name/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://jmilic/model_name/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jmilic/model_name/resolve/main/pytorch_model.bin
505 MB
- Xet hash:
- b54ad1483cc74c45357521d92f7abfdcd9de1766e869ff1306fd5c2354d85902
- Size of remote file:
- 505 MB
- SHA256:
- 1ecc67c53ac0ed8cf8b6edd2f6db471bf5948d16c1edb08e029103c8597987b2
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