Text Classification
PEFT
PyTorch
Safetensors
English
regression
story-point-estimation
software-engineering
Eval Results (legacy)
Instructions to use DEVCamiloSepulveda/2-LLAMA3SP-titanium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DEVCamiloSepulveda/2-LLAMA3SP-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/2-LLAMA3SP-titanium") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6a25492cbaaa8753169a8a8b5736905360f9e194d6434998809a46118b8dac58
- Size of remote file:
- 1.56 GB
- SHA256:
- 86e874ecf951a750eb1c9f6ceed6cf216c6a82c54934efd216a0b16d12972f97
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