Instructions to use henrynguyen13/text-to-sql with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use henrynguyen13/text-to-sql with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("Salesforce/codet5-base") model = PeftModel.from_pretrained(base_model, "henrynguyen13/text-to-sql") - Notebooks
- Google Colab
- Kaggle
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Download README.md from henrynguyen13/text-to-sql: direct link, hf CLI and curl.
- Browser
- Download file 1.16 kB
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https://huggingface.co/henrynguyen13/text-to-sql/resolve/main/README.md
- Command line
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hf download hf://henrynguyen13/text-to-sql/README.md
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curl -L -o README.md https://huggingface.co/henrynguyen13/text-to-sql/resolve/main/README.md
1.16 kB
| library_name: peft | |
| license: apache-2.0 | |
| base_model: Salesforce/codet5-base | |
| tags: | |
| - generated_from_trainer | |
| model-index: | |
| - name: text-to-sql | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # text-to-sql | |
| This model is a fine-tuned version of [Salesforce/codet5-base](https://huggingface.co/Salesforce/codet5-base) on an unknown dataset. | |
| ## Model description | |
| More information needed | |
| ## Intended uses & limitations | |
| More information needed | |
| ## Training and evaluation data | |
| More information needed | |
| ## Training procedure | |
| ### Training hyperparameters | |
| The following hyperparameters were used during training: | |
| - learning_rate: 0.001 | |
| - train_batch_size: 32 | |
| - eval_batch_size: 32 | |
| - seed: 42 | |
| - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments | |
| - lr_scheduler_type: linear | |
| - num_epochs: 1 | |
| ### Training results | |
| ### Framework versions | |
| - PEFT 0.14.0 | |
| - Transformers 4.47.0 | |
| - Pytorch 2.5.1+cu121 | |
| - Datasets 3.3.1 | |
| - Tokenizers 0.21.0 |