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TencentARC_-_Mistral_Pro_8B_v0.1-gguf
RichardErkhov/TencentARC_-_Mistral_Pro_8B_v0.1-gguf
TencentARC_-_Mistral_Pro_8B_v0.1-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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.gguf118 GB · 100%
At a glance
- Access
- Public
- Created
- May 24, 2024
- Updated
- May 24, 2024
- SHA
- 4677ffbe
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
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.
- Created
- May 24, 2024
- Updated
- May 24, 2024