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RichardErkhov/
TencentARC_-_Mistral_Pro_8B_v0.1-gguf

Name: TencentARC_-_Mistral_Pro_8B_v0.1-gguf
Availability: InStock

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Mistral_Pro_8B_v0.1 - GGUF

Model creator: https://huggingface.co/TencentARC/
Original model: https://huggingface.co/TencentARC/Mistral_Pro_8B_v0.1/

Name	Quant method	Size
Mistral_Pro_8B_v0.1.Q2_K.gguf	Q2_K	3.13GB
Mistral_Pro_8B_v0.1.IQ3_XS.gguf	IQ3_XS	3.48GB
Mistral_Pro_8B_v0.1.IQ3_S.gguf	IQ3_S	3.67GB
Mistral_Pro_8B_v0.1.Q3_K_S.gguf	Q3_K_S	3.65GB
Mistral_Pro_8B_v0.1.IQ3_M.gguf	IQ3_M	3.79GB
Mistral_Pro_8B_v0.1.Q3_K.gguf	Q3_K	4.05GB
Mistral_Pro_8B_v0.1.Q3_K_M.gguf	Q3_K_M	4.05GB
Mistral_Pro_8B_v0.1.Q3_K_L.gguf	Q3_K_L	4.41GB
Mistral_Pro_8B_v0.1.IQ4_XS.gguf	IQ4_XS	4.55GB
Mistral_Pro_8B_v0.1.Q4_0.gguf	Q4_0	4.74GB
Mistral_Pro_8B_v0.1.IQ4_NL.gguf	IQ4_NL	4.79GB
Mistral_Pro_8B_v0.1.Q4_K_S.gguf	Q4_K_S	4.78GB
Mistral_Pro_8B_v0.1.Q4_K.gguf	Q4_K	5.04GB
Mistral_Pro_8B_v0.1.Q4_K_M.gguf	Q4_K_M	5.04GB
Mistral_Pro_8B_v0.1.Q4_1.gguf	Q4_1	5.26GB
Mistral_Pro_8B_v0.1.Q5_0.gguf	Q5_0	5.77GB
Mistral_Pro_8B_v0.1.Q5_K_S.gguf	Q5_K_S	5.77GB
Mistral_Pro_8B_v0.1.Q5_K.gguf	Q5_K	5.93GB
Mistral_Pro_8B_v0.1.Q5_K_M.gguf	Q5_K_M	5.93GB
Mistral_Pro_8B_v0.1.Q5_1.gguf	Q5_1	6.29GB
Mistral_Pro_8B_v0.1.Q6_K.gguf	Q6_K	6.87GB
Mistral_Pro_8B_v0.1.Q8_0.gguf	Q8_0	8.89GB

Original model description:

license: apache-2.0 datasets:

HuggingFaceTB/cosmopedia
EleutherAI/proof-pile-2
bigcode/the-stack-dedup
math-ai/AutoMathText language:
en metrics:
accuracy
code_eval

Mistral-Pro-8B Model Card

Model Description

Mistral-Pro is a progressive version of the original Mistral 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.

Development and Training

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.

Intended Use

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.

Performance

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.

Overall Performance on Languages, math and code tasks

Model	ARC	Hellaswag	MMLU	TruthfulQA	Winogrande	GSM8K	HumanEval
Gemma-7B	61.9	82.2	64.6	44.8	79.0	50.9	32.3
Mistral-7B	60.8	83.3	62.7	42.6	78.0	39.2	28.7
Mistral_Pro_8B_v0.1	63.2	82.6	60.6	48.3	78.9	50.6	32.9

Limitations

While Mistral-Pro addresses some limitations of previous models in the series, it may still encounter challenges specific to highly specialized domains or tasks.

Ethical Considerations

Users should be aware of potential biases in the model and use it responsibly, considering its impact on various applications.

RichardErkhov/TencentARC_-_Mistral_Pro_8B_v0.1-gguf