Text Classification
PEFT
PyTorch
Safetensors
English
regression
story-point-estimation
software-engineering
Eval Results (legacy)
Instructions to use DEVCamiloSepulveda/3-Qwen3SP-titanium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DEVCamiloSepulveda/3-Qwen3SP-titanium with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("Qwen/Qwen3-1.7B") model = PeftModel.from_pretrained(base_model, "DEVCamiloSepulveda/3-Qwen3SP-titanium") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 348bc27e2f43898c4a739eaa029ffce8c113d927bbc33cc553915c0287bb4faa
- Size of remote file:
- 1.99 GB
- SHA256:
- c766b3ab82ab3c9471b1c41440e6083c80477ebce2141b0d704d5cb568cfeb3c
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