Instructions to use codegenstudio/codegen-350M-text2sql-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use codegenstudio/codegen-350M-text2sql-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/kaggle/working/models/base/Salesforce__codegen-350M-multi") model = PeftModel.from_pretrained(base_model, "codegenstudio/codegen-350M-text2sql-lora") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-1006/optimizer.pt from codegenstudio/codegen-350M-text2sql-lora: direct link, hf CLI and curl.
- Browser
- Download file 84 MB
-
https://huggingface.co/codegenstudio/codegen-350M-text2sql-lora/resolve/21394e2465c6da6059048855c62cebdc9fbb29df/checkpoint-1006/optimizer.pt
- Command line
-
hf download hf://codegenstudio/codegen-350M-text2sql-lora@21394e2465c6da6059048855c62cebdc9fbb29df/checkpoint-1006/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/codegenstudio/codegen-350M-text2sql-lora/resolve/21394e2465c6da6059048855c62cebdc9fbb29df/checkpoint-1006/optimizer.pt
84 MB
- Xet hash:
- 7d0241a22dd9eb6f748879243cf7cbbe76891e6de7035871f5f0e154b1df76e8
- Size of remote file:
- 84 MB
- SHA256:
- ecfc8a4189800760f4908770a0fe06c314be80407500263c8605aef1ab433402
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