Text Classification
PEFT
PyTorch
Safetensors
English
regression
story-point-estimation
software-engineering
Eval Results (legacy)
Instructions to use DEVCamiloSepulveda/66-LLAMA3SP-aptanastudio-titanium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DEVCamiloSepulveda/66-LLAMA3SP-aptanastudio-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/66-LLAMA3SP-aptanastudio-titanium") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 250181aaabd99c1f6fa33bf15c73a0e94bd05a792ccff0b083d2935c05a63944
- Size of remote file:
- 1.56 GB
- SHA256:
- d3512596b379c5fb345b7066cdf4c62346ddc76f5cbe8333ed9602087a09e783
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