Instructions to use champ7/gemma-text-to-sql with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use champ7/gemma-text-to-sql with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("champ7/gemma-text-to-sql", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files
README.md
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model_name: gemma-text-to-sql
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tags:
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- generated_from_trainer
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- trl
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- sft
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licence: license
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---
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- TRL: 1.1.0
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- Transformers: 5.5.4
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- Pytorch: 2.
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- Datasets: 4.8.4
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- Tokenizers: 0.22.2
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model_name: gemma-text-to-sql
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tags:
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- generated_from_trainer
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- sft
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- trl
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licence: license
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---
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- TRL: 1.1.0
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- Transformers: 5.5.4
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- Pytorch: 2.9.0+cu128
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- Datasets: 4.8.4
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- Tokenizers: 0.22.2
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adapter_config.json
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"rank_pattern": {},
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"task_type": "CAUSAL_LM",
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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adapter_model.safetensors
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runs/Apr15_09-04-28_c7c13e1df0c6/events.out.tfevents.1776243868.c7c13e1df0c6.15979.0
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