Text Classification
PEFT
PyTorch
Safetensors
English
regression
story-point-estimation
software-engineering
Eval Results (legacy)
Instructions to use DEVCamiloSepulveda/00-LLAMA3SP-mule-mulestudio with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DEVCamiloSepulveda/00-LLAMA3SP-mule-mulestudio 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/00-LLAMA3SP-mule-mulestudio") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dcdfeb664785edeea8acb49b7c9cd665fd26de40abba79eabac46ba57d02729a
- Size of remote file:
- 1.56 GB
- SHA256:
- 9210ece6a622f9a6359d60755c38c1dc8fd51762c347a17cdf50a0e004e4a6f9
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