Text Classification
PEFT
PyTorch
Safetensors
English
regression
story-point-estimation
software-engineering
Eval Results (legacy)
Instructions to use DEVCamiloSepulveda/00-LLAMA3SP-appceleratorstudio-titanium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DEVCamiloSepulveda/00-LLAMA3SP-appceleratorstudio-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/00-LLAMA3SP-appceleratorstudio-titanium") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e631f0d6459a3e9280e5a0997cb4c092282d204d77a4d6911304748c6f705462
- Size of remote file:
- 1.56 GB
- SHA256:
- 175df0c750f65329008bd3a9a323509ac2c1e5310c6bc64d7865f007bee055a5
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