Instructions to use vidyamdeveloper/NLQ_dataset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use vidyamdeveloper/NLQ_dataset with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("nvidia/Llama-3.1-Nemotron-Nano-8B-v1") model = PeftModel.from_pretrained(base_model, "vidyamdeveloper/NLQ_dataset") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d96cf3f136bb5b10ffbb04893daecc0bc8040809e191bcdec35fc7f440622c09
- Size of remote file:
- 5.5 kB
- SHA256:
- 91769ad0952b65833fd598bf166eb7749c223af66f35f395bdd18d527a7f8b81
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