Text Classification
PEFT
PyTorch
Safetensors
English
regression
story-point-estimation
software-engineering
Eval Results (legacy)
Instructions to use DEVCamiloSepulveda/33-Qwen3SP-usergrid-mesos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DEVCamiloSepulveda/33-Qwen3SP-usergrid-mesos 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/33-Qwen3SP-usergrid-mesos") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9fc3ac12eeaba8facffd10d0ef3ad43a3b9029cfb8ff7ae584169282498e9a96
- Size of remote file:
- 1.99 GB
- SHA256:
- 78978fca2b5d95b4963988b4c05ffe66ca3de70031e243c7307450a09d0f0692
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