Text Classification
PEFT
PyTorch
Safetensors
English
regression
story-point-estimation
software-engineering
Eval Results (legacy)
Instructions to use DEVCamiloSepulveda/7-LLAMA3SP-mule with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DEVCamiloSepulveda/7-LLAMA3SP-mule with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("meta-llama/Llama-3.2-1B") model = PeftModel.from_pretrained(base_model, "DEVCamiloSepulveda/7-LLAMA3SP-mule") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6742b4e54196f8566685a870d4d6f819bf9a415294ef5b9a7cf27267ef1ee26c
- Size of remote file:
- 1.56 GB
- SHA256:
- 32f89aa4137182695ef5888502f00abc52159994fdb34f46e36fb196491ea193
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