Instructions to use Vanbitcase/lora_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vanbitcase/lora_model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Vanbitcase/lora_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from Vanbitcase/lora_model: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/Vanbitcase/lora_model/resolve/main/tokenizer.json
- Command line
-
hf download hf://Vanbitcase/lora_model/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Vanbitcase/lora_model/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 19bd125947c8acedb2e7a6ca3943d4627a466da3b21681abdcfeb638ba070bea
- Size of remote file:
- 11.4 MB
- SHA256:
- 0b078bef7228024a62191028fb7c2e9edf92793dd95c561b5cb47c53faf2d9ed
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