Instructions to use selimyagci/pm_task_llama_quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use selimyagci/pm_task_llama_quantized with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("meta-llama/Llama-3.2-1B") model.load_adapter("selimyagci/pm_task_llama_quantized", set_active=True) - Notebooks
- Google Colab
- Kaggle
Download pytorch_model_head.bin from selimyagci/pm_task_llama_quantized: direct link, hf CLI and curl.
- Browser
- Download file 525 MB
-
https://huggingface.co/selimyagci/pm_task_llama_quantized/resolve/main/pytorch_model_head.bin
- Command line
-
hf download hf://selimyagci/pm_task_llama_quantized/pytorch_model_head.bin
-
curl -L -o pytorch_model_head.bin https://huggingface.co/selimyagci/pm_task_llama_quantized/resolve/main/pytorch_model_head.bin
525 MB
- Xet hash:
- a1968f3dda33da11e85c0a8f894795fe235dfaaccea09696e30d0344d5d8cc46
- Size of remote file:
- 525 MB
- SHA256:
- c78294289997f2d22eb8c7f66a6e8815a4e60ed3594562b5bd706da12739e0bc
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