Instructions to use kamel-usp/jbcs2025_Llama-3.1-8B-llama31_classification_lora-C1-full_context-r16 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-C1-full_context-r16 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-C1-full_context-r16") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from kamel-usp/jbcs2025_Llama-3.1-8B-llama31_classification_lora-C1-full_context-r16: direct link, hf CLI and curl.
- Browser
- Download file 168 MB
-
https://huggingface.co/kamel-usp/jbcs2025_Llama-3.1-8B-llama31_classification_lora-C1-full_context-r16/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://kamel-usp/jbcs2025_Llama-3.1-8B-llama31_classification_lora-C1-full_context-r16/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/kamel-usp/jbcs2025_Llama-3.1-8B-llama31_classification_lora-C1-full_context-r16/resolve/main/adapter_model.safetensors
168 MB
- Xet hash:
- 3491c8c1582c90021ec1ccf00da28f31b0d4f1dbdebf3308a8aa9a09e16dafb3
- Size of remote file:
- 168 MB
- SHA256:
- c040627712c2ce94a18d9727831f267b1ce36808cf02c6f7fed2449e3ad1064b
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