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 training_args.bin from jmilic/model_name: direct link, hf CLI and curl.
- Browser
- Download file 3.06 kB
-
https://huggingface.co/jmilic/model_name/resolve/main/training_args.bin
- Command line
-
hf download hf://jmilic/model_name/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jmilic/model_name/resolve/main/training_args.bin
3.06 kB
- Xet hash:
- 1a8e07a17c6f1a97b6b5b171dfd5d04aaf5a1135ec71e1723324595c3c9bb12f
- Size of remote file:
- 3.06 kB
- SHA256:
- 20a4fcb54e7e28b0c2515f651824ad95ebdea4bfd3237c8acdd46d87035be8c7
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