Instructions to use kamel-usp/jbcs2025_Llama-3.1-8B-llama31_classification_lora-C5-full_context with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kamel-usp/jbcs2025_Llama-3.1-8B-llama31_classification_lora-C5-full_context with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("meta-llama/Llama-3.1-8B") model = PeftModel.from_pretrained(base_model, "kamel-usp/jbcs2025_Llama-3.1-8B-llama31_classification_lora-C5-full_context") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from kamel-usp/jbcs2025_Llama-3.1-8B-llama31_classification_lora-C5-full_context: direct link, hf CLI and curl.
- Browser
- Download file 84 MB
-
https://huggingface.co/kamel-usp/jbcs2025_Llama-3.1-8B-llama31_classification_lora-C5-full_context/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://kamel-usp/jbcs2025_Llama-3.1-8B-llama31_classification_lora-C5-full_context/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/kamel-usp/jbcs2025_Llama-3.1-8B-llama31_classification_lora-C5-full_context/resolve/main/adapter_model.safetensors
84 MB
- Xet hash:
- 30e243e8f2458eeb51d6803c132f8f2fa66e4e79a0c3bde18ec5fbf76240b1b4
- Size of remote file:
- 84 MB
- SHA256:
- bf931695c47a0d964eb73ce463a361fe33a10e83bc38eb2daf5cdd16bfb03a79
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