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:
- 8ea3fb5189fdbf09f8e22d6630c8337a5d0090b561f8cb6d0ecc0e8706592c13
- Size of remote file:
- 2.68 GB
- SHA256:
- 51991c257c9be6ba6f27540a3cb68975e32d4de44d06a0c5a978785b803176d9
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