Instructions to use lentohaihane/r-4b-sft-code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lentohaihane/r-4b-sft-code with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("lentohaihane/r-4b-sft-code", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from lentohaihane/r-4b-sft-code: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/lentohaihane/r-4b-sft-code/resolve/main/tokenizer.json
- Command line
-
hf download hf://lentohaihane/r-4b-sft-code/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/lentohaihane/r-4b-sft-code/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- d746390c0ab9e62475e4578d980dedddbc424f6ec09bb1b2517389fb3b25e3dd
- Size of remote file:
- 11.4 MB
- SHA256:
- a44bdeb203b51e0bc7615c0e920f5278ebdac0a51146a9177a3d428030305168
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