Instructions to use 2xionger/code-llama-7b-text-to-sql with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use 2xionger/code-llama-7b-text-to-sql with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("codellama/CodeLlama-7b-hf") model = PeftModel.from_pretrained(base_model, "2xionger/code-llama-7b-text-to-sql") - Notebooks
- Google Colab
- Kaggle
| { | |
| "additional_special_tokens": [ | |
| { | |
| "content": "<|im_start|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| { | |
| "content": "<|im_end|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| } | |
| ], | |
| "bos_token": "<|im_start|>", | |
| "eos_token": "<|im_end|>", | |
| "pad_token": "<|im_end|>", | |
| "unk_token": { | |
| "content": "<unk>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| } | |
| } | |