Text Classification
PEFT
PyTorch
Safetensors
English
regression
story-point-estimation
software-engineering
Eval Results (legacy)
Instructions to use DEVCamiloSepulveda/000-LLAMA3SP-mulestudio-titanium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DEVCamiloSepulveda/000-LLAMA3SP-mulestudio-titanium 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/000-LLAMA3SP-mulestudio-titanium") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f3f3bcdbbbd6f34e6b16653915beaf1518244887bb06d2b0fe97bf9590d0e348
- Size of remote file:
- 1.56 GB
- SHA256:
- 4d338b02e8bc3591069365a901dadb6251fcd6f663a1605132c0d5f69849d8e8
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