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Model: TencentARC/Mistral_Pro_8B_v0.1 Source: Original Platform
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README.md
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license: apache-2.0
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datasets:
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- HuggingFaceTB/cosmopedia
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- EleutherAI/proof-pile-2
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- bigcode/the-stack-dedup
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- math-ai/AutoMathText
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language:
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- en
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metrics:
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- accuracy
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- code_eval
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---
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# Mistral-Pro-8B Model Card
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## Model Description
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Mistral-Pro is a progressive version of the original [Mistral](https://huggingface.co/mistralai/Mistral-7B-v0.1) model, enhanced by the addition of Transformer blocks. It specializes in integrating both general language understanding and domain-specific knowledge, particularly in programming and mathematics.
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## Development and Training
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Developed by Tencent's ARC Lab, Mistral-Pro is an 8 billion parameter model. It's an expansion of Mistral-7B, further trained on code and math corpora.
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## Intended Use
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This model is designed for a wide range of NLP tasks, with a focus on programming, mathematics, and general language tasks. It suits scenarios requiring integration of natural and programming languages.
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## Performance
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Mistral_Pro_8B_v0.1 showcases superior performance on a range of benchmarks. It enhances the code and math performance of Mistral. Furthermore, it matches the performance of the recently dominant model, [Gemma](https://huggingface.co/google/gemma-7b).
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### Overall Performance on Languages, math and code tasks
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| Model | ARC | Hellaswag | MMLU | TruthfulQA | Winogrande | GSM8K | HumanEval |
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| :-: | :-: | :-: | :-: | :-: | :-: | :-: | :-: |
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| Gemma-7B | 61.9 | 82.2 | 64.6 | 44.8 | 79.0 | 50.9 | 32.3 |
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| Mistral-7B | 60.8 | 83.3 | 62.7 | 42.6 | 78.0 | 39.2 | 28.7 |
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| Mistral_Pro_8B_v0.1 | 63.2 | 82.6 | 60.6 | 48.3 | 78.9 | 50.6 | 32.9 |
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## Limitations
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While Mistral-Pro addresses some limitations of previous models in the series, it may still encounter challenges specific to highly specialized domains or tasks.
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## Ethical Considerations
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Users should be aware of potential biases in the model and use it responsibly, considering its impact on various applications.
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