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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
+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](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.
+
+## 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](https://huggingface.co/google/gemma-7b).
+
+### 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.

config.json

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+{
+  "architectures": [
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+  ],
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+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 32768,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 40,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.34.0.dev0",
+  "use_cache": true,
+  "vocab_size": 32000
+}

configuration.json

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+{"framework": "pytorch", "task": "text-generation", "allow_remote": true}

generation_config.json

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+  "transformers_version": "4.34.0.dev0"
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special_tokens_map.json

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tokenizer_config.json

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