Instructions to use Liu-Xiang/sql-code-llama with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Liu-Xiang/sql-code-llama 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, "Liu-Xiang/sql-code-llama") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from Liu-Xiang/sql-code-llama: direct link, hf CLI and curl.
- Browser
- Download file 48 Bytes
-
https://huggingface.co/Liu-Xiang/sql-code-llama/resolve/67c24ded5e17c404faa8aaf5efe28dcafe89526d/adapter_model.safetensors
- Command line
-
hf download hf://Liu-Xiang/sql-code-llama@67c24ded5e17c404faa8aaf5efe28dcafe89526d/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/Liu-Xiang/sql-code-llama/resolve/67c24ded5e17c404faa8aaf5efe28dcafe89526d/adapter_model.safetensors
48 Bytes
- Xet hash:
- dbfdb4c44e886525fb5a80e927a01c64e2afcda8f2c7efe4da9d27996bf8b6e4
- Size of remote file:
- 48 Bytes
- SHA256:
- e44ce263e6fd885f50d82ca515b9325375b43ee36ededb75acf161ce88bc2e41
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