Instructions to use Shibyan/llama3.1_Odata2SQL-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Shibyan/llama3.1_Odata2SQL-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3.1-8B-Instruct") model = PeftModel.from_pretrained(base_model, "Shibyan/llama3.1_Odata2SQL-lora") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-30/tokenizer.json from Shibyan/llama3.1_Odata2SQL-lora: direct link, hf CLI and curl.
- Browser
- Download file 9.09 MB
-
https://huggingface.co/Shibyan/llama3.1_Odata2SQL-lora/resolve/main/checkpoint-30/tokenizer.json
- Command line
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hf download hf://Shibyan/llama3.1_Odata2SQL-lora/checkpoint-30/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/Shibyan/llama3.1_Odata2SQL-lora/resolve/main/checkpoint-30/tokenizer.json
9.09 MB
File too large to display, you can check the raw version instead.