Instructions to use vsrinivas/TinyLLAMA_VS_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vsrinivas/TinyLLAMA_VS_test with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("vsrinivas/TinyLLAMA_VS_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download adapter_model.safetensors from vsrinivas/TinyLLAMA_VS_test: direct link, hf CLI and curl.
- Browser
- Download file 575 MB
-
https://huggingface.co/vsrinivas/TinyLLAMA_VS_test/resolve/495658abc6efd242cd5eecaa1cdc55262d94bd0e/adapter_model.safetensors
- Command line
-
hf download hf://vsrinivas/TinyLLAMA_VS_test@495658abc6efd242cd5eecaa1cdc55262d94bd0e/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/vsrinivas/TinyLLAMA_VS_test/resolve/495658abc6efd242cd5eecaa1cdc55262d94bd0e/adapter_model.safetensors
575 MB
- Xet hash:
- d6cb2cd0f0a9358f5b19333458b2456baddd4c6cdcb43225835cb6e8cc20757d
- Size of remote file:
- 575 MB
- SHA256:
- 912899dd71767c34d5029287a43c2cab2076a6bee01ce3267383f2ee6c9a3955
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.