Instructions to use cwaud/29a9a50b-b225-4aac-afd7-8d1228fe1ff4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use cwaud/29a9a50b-b225-4aac-afd7-8d1228fe1ff4 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Hermes-3-Llama-3.1-8B") model = PeftModel.from_pretrained(base_model, "cwaud/29a9a50b-b225-4aac-afd7-8d1228fe1ff4") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from cwaud/29a9a50b-b225-4aac-afd7-8d1228fe1ff4: direct link, hf CLI and curl.
- Browser
- Download file 84 MB
-
https://huggingface.co/cwaud/29a9a50b-b225-4aac-afd7-8d1228fe1ff4/resolve/main/adapter_model.bin
- Command line
-
hf download hf://cwaud/29a9a50b-b225-4aac-afd7-8d1228fe1ff4/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/cwaud/29a9a50b-b225-4aac-afd7-8d1228fe1ff4/resolve/main/adapter_model.bin
84 MB
- Xet hash:
- fee7fa8e296a3c46e2490ade1a636fc752a961dede89dec786427ff2fc7cedb8
- Size of remote file:
- 84 MB
- SHA256:
- 3bf80e2f5abb39b4aff0c960006bb2686ce8675a5c15747dbefed6d4febdc5d7
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