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_adapter.bin from selimyagci/pm_task_llama_quantized: direct link, hf CLI and curl.
- Browser
- Download file 33.7 MB
-
https://huggingface.co/selimyagci/pm_task_llama_quantized/resolve/main/pytorch_adapter.bin
- Command line
-
hf download hf://selimyagci/pm_task_llama_quantized/pytorch_adapter.bin
-
curl -L -o pytorch_adapter.bin https://huggingface.co/selimyagci/pm_task_llama_quantized/resolve/main/pytorch_adapter.bin
33.7 MB
- Xet hash:
- 6fb3526a3049f4f17bec80e8b7d7bcae405355a3e3d9ee11b310d6b288bd6d6b
- Size of remote file:
- 33.7 MB
- SHA256:
- f70abfa7af5dffc2e8a12857e13a6e423288a112f44e4aa1ef8a2e26a5806014
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