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Model: uukuguy/speechless-mistral-six-in-one-7b Source: Original Platform
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README.md
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README.md
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---
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language:
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- en
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library_name: transformers
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pipeline_tag: text-generation
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datasets:
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- jondurbin/airoboros-2.2.1
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- Open-Orca/OpenOrca
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- garage-bAInd/Open-Platypus
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- ehartford/samantha-data
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- CollectiveCognition/chats-data-2023-09-27
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- stingning/ultrachat
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tags:
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- llama-2
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- code
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license: llama2
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model-index:
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- name: SpeechlessCoder
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results:
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- task:
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type: text-generation
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dataset:
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type: openai_humaneval
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name: HumanEval
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metrics:
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- name: pass@1
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type: pass@1
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value: 0.0
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verified: false
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---
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<p><h1> speechless-mistral-six-in-one-7b </h1></p>
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This model is a merge of 6 SOTA Mistral-7B based models:
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- ehartford/dolphin-2.1-mistral-7b
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- Open-Orca/Mistral-7B-OpenOrca
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- bhenrym14/mistral-7b-platypus-fp16
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- ehartford/samantha-1.2-mistral-7b
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- iteknium/CollectiveCognition-v1.1-Mistral-7B
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- HuggingFaceH4/zephyr-7b-alpha
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[Model benchmark](https://huggingface.co/uukuguy/speechless-mistral-six-in-one-7b/discussions/1) by [sethuiyer](https://huggingface.co/sethuiyer) . Thanks a lot.
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> I tested the Q6_0 version of the model against LLaMa2 70B chat and here are the results - Scoring as per ChatGPT and Bard's average. Named this model Mixtral. Questions taken from MT-Benchmark.
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>
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> On a scale of 0 to 100, I would rate Mixtral at 98. Here's why:
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>
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> - Intellect (100/100) - Mixtral has demonstrated immense intellectual abilities through its comprehensive knowledge and logical reasoning skills.
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> - Creativity (98/100) - In addition to being highly intelligent, Mixtral also displays impressive creative talents through its unique, nuanced responses.
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> - Adaptability (98/100) - Mixtral can converse flexibly on a wide variety of topics, adapting smoothly based on contextual cues.
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> - Communication (97/100) - Mixtral communicates clearly and eloquently through written language, thoroughly answering questions.
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> - Problem-Solving (98/100) - Questions are addressed comprehensively, considering multiple perspectives to arrive at well-thought solutions.
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> - Personability (97/100) - Responses are warm, inviting and non-threatening due to Mixtral's kindness and thoughtfulness.
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>
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> Overall, a very capable model for it's size.
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Code: https://github.com/uukuguy/speechless
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## HumanEval
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| Metric | Value |
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| --- | --- |
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| humaneval-python | |
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[Big Code Models Leaderboard](https://huggingface.co/spaces/bigcode/bigcode-models-leaderboard)
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CodeLlama-34B-Python: 53.29
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CodeLlama-34B-Instruct: 50.79
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CodeLlama-13B-Instruct: 50.6
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CodeLlama-34B: 45.11
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CodeLlama-13B-Python: 42.89
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CodeLlama-13B: 35.07
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Mistral-7B-v0.1: 30.488
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## LM-Evaluation-Harness
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[Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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| Metric | Value |
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| --- | --- |
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| ARC | 62.97 |
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| HellaSwag | 84.6|
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| MMLU | 63.29 |
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| TruthfulQA | 57.77 |
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| Winogrande | 77.51 |
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| GSM8K | 18.42 |
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| DROP | 9.13 |
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| Average | 53.38 |
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# Model Card for Mistral-7B-v0.1
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The Mistral-7B-v0.1 Large Language Model (LLM) is a pretrained generative text model with 7 billion parameters.
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Mistral-7B-v0.1 outperforms Llama 2 13B on all benchmarks we tested.
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For full details of this model please read our [paper](https://arxiv.org/abs/2310.06825) and [release blog post](https://mistral.ai/news/announcing-mistral-7b/).
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## Model Architecture
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Mistral-7B-v0.1 is a transformer model, with the following architecture choices:
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- Grouped-Query Attention
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- Sliding-Window Attention
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- Byte-fallback BPE tokenizer
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## Troubleshooting
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- If you see the following error:
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``
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KeyError: 'mistral'
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``
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- Or:
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``
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NotImplementedError: Cannot copy out of meta tensor; no data!
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``
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Ensure you are utilizing a stable version of Transformers, 4.34.0 or newer.
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## Notice
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Mistral 7B is a pretrained base model and therefore does not have any moderation mechanisms.
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## The Mistral AI Team
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Albert Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lélio Renard Lavaud, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, William El Sayed.`
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_uukuguy__speechless-mistral-six-in-one-7b)
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| Metric | Value |
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|-----------------------|---------------------------|
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| Avg. | 53.38 |
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| ARC (25-shot) | 62.97 |
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| HellaSwag (10-shot) | 84.6 |
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| MMLU (5-shot) | 63.29 |
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| TruthfulQA (0-shot) | 57.77 |
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| Winogrande (5-shot) | 77.51 |
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| GSM8K (5-shot) | 18.42 |
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| DROP (3-shot) | 9.13 |
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