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README.md
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# Mistral-7B-codealpaca
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## Training Details
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[](https://github.com/OpenAccess-AI-Collective/axolotl)
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## Quantised Model Links:
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1.
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Well, the results are better than I expected
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- Base: `{'pass@1': 0.47560975609756095}`
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- Base + Extra: `{'pass@1': 0.4329268292682927}`
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For reference,
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** [Nondzu/Mistral-7B-code-16k-qlora](https://huggingface.co/Nondzu/Mistral-7B-code-16k-qlora)**:
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## Model Configuration:
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```yaml
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base_model: mistralai/Mistral-7B-Instruct-v0.1
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lora_target_linear: true
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```
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## Additional Projects:
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For other related projects, you can check out:
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# Mistral-7B-codealpaca
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I am thrilled to introduce my Mistral-7B-codealpaca model. This variant is optimized and demonstrates potential in assisting developers as a coding companion. I welcome contributions from testers and enthusiasts to help evaluate its performance.
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## Training Details
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I trained the model using 3xRTX 3090 for 118 hours.
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[](https://github.com/OpenAccess-AI-Collective/axolotl)
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## Quantised Model Links:
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1.
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Well, the results are better than I expected:
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- Base: `{'pass@1': 0.47560975609756095}`
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- Base + Extra: `{'pass@1': 0.4329268292682927}`
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For reference, I've provided the performance of the original Mistral model alongside my Mistral-7B-code-16k-qlora model.
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** [Nondzu/Mistral-7B-code-16k-qlora](https://huggingface.co/Nondzu/Mistral-7B-code-16k-qlora)**:
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## Model Configuration:
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Here are the configurations for my Mistral-7B-codealpaca-lora:
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```yaml
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base_model: mistralai/Mistral-7B-Instruct-v0.1
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lora_target_linear: true
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```
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## Additional Projects:
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For other related projects, you can check out:
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