Instructions to use kamel-usp/jbcs2025_Llama-3.1-8B-llama31_classification_lora-C2-essay_only-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-C2-essay_only-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-C2-essay_only-r16") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from kamel-usp/jbcs2025_Llama-3.1-8B-llama31_classification_lora-C2-essay_only-r16: direct link, hf CLI and curl.
- Browser
- Download file 5.84 kB
-
https://huggingface.co/kamel-usp/jbcs2025_Llama-3.1-8B-llama31_classification_lora-C2-essay_only-r16/resolve/main/training_args.bin
- Command line
-
hf download hf://kamel-usp/jbcs2025_Llama-3.1-8B-llama31_classification_lora-C2-essay_only-r16/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/kamel-usp/jbcs2025_Llama-3.1-8B-llama31_classification_lora-C2-essay_only-r16/resolve/main/training_args.bin
5.84 kB
- Xet hash:
- 08847ecbfb4f7dfd8a72859411f37f935004c0afc59ad9864f08001caf8738bc
- Size of remote file:
- 5.84 kB
- SHA256:
- 851ee078b24eb9ad113408f54a11433613633206637558fc1f373898be63a641
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