Instructions to use jamesphe/lora_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jamesphe/lora_model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jamesphe/lora_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download adapter_model.safetensors from jamesphe/lora_model: direct link, hf CLI and curl.
- Browser
- Download file 160 MB
-
https://huggingface.co/jamesphe/lora_model/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://jamesphe/lora_model/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/jamesphe/lora_model/resolve/main/adapter_model.safetensors
160 MB
- Xet hash:
- 43b5bf41f85af4150ddd127bbe30439a4e56c8d276d49781b9585da326d8fc6e
- Size of remote file:
- 160 MB
- SHA256:
- 7a037fc74049ca914909ed0f29b3c8b9757b6857efeaeeb77636a4f7fc492dfa
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