Instructions to use nomadrp/msimpo-10each with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nomadrp/msimpo-10each with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nomadrp/msimpo-10each", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from nomadrp/msimpo-10each: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/nomadrp/msimpo-10each/resolve/main/tokenizer.json
- Command line
-
hf download hf://nomadrp/msimpo-10each/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/nomadrp/msimpo-10each/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- 841d91ad71224eab8e3f26ca79dc2e83e52c9107712c6a7b737e41b082869326
- Size of remote file:
- 17.2 MB
- SHA256:
- 5edccccebf9dd135e2ef1719f106217d964321f6ec33f6eb0a27347b17e22346
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