Instructions to use kamel-usp/jbcs2025_Tucano-2b4-Instruct-tucano_classification_lora-C2-full_context-r8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kamel-usp/jbcs2025_Tucano-2b4-Instruct-tucano_classification_lora-C2-full_context-r8 with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("TucanoBR/Tucano-2b4-Instruct") model = PeftModel.from_pretrained(base_model, "kamel-usp/jbcs2025_Tucano-2b4-Instruct-tucano_classification_lora-C2-full_context-r8") - Notebooks
- Google Colab
- Kaggle
jbcs2025_Tucano-2b4-Instruct-tucano_classification_lora-C2-full_context-r8 / adapter_model.safetensors
- Xet hash:
- a599eb80deb1ed4c118e26869f8eef830e015d679f150e9b51d270bf110315e6
- Size of remote file:
- 42.4 MB
- SHA256:
- bc4961d22bbe3616d2e829c51c853506324e3dba713db233d95b69f05064b6ef
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