Instructions to use Maaz66/mistral_python_instruct_140_rows_QnA_Rating with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Maaz66/mistral_python_instruct_140_rows_QnA_Rating with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2") model = PeftModel.from_pretrained(base_model, "Maaz66/mistral_python_instruct_140_rows_QnA_Rating") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 23be1368b559beebeb04efd1f1ff5509e6ff6ff76982f7a5f0c088309a8ce20e
- Size of remote file:
- 369 MB
- SHA256:
- 3e40daf7a529710092fdbf73873bf1b14f340ad2c034b509b78f77fee130adb2
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