Instructions to use Navot9196/mistral-7b-sql-qlora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Navot9196/mistral-7b-sql-qlora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.1") model = PeftModel.from_pretrained(base_model, "Navot9196/mistral-7b-sql-qlora") - Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
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README.md
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# Model Card for
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- **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Finetuned from model [optional]:**
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### Model Sources [optional]
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base_model: mistralai/Mistral-7B-v0.1
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tags:
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- text-to-sql
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- qlora
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- mistral
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- peft
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# Model Card for Navot9196/mistral-7b-sql-qlora
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<!-- Provide a quick summary of what the model is/does. -->
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Mistral-7B finetuned with QLoRA on text-to-SQL (b-mc2/sql-create-context)
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- **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** mistralai/Mistral-7B-v0.1
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### Model Sources [optional]
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