151 lines
4.7 KiB
Markdown
151 lines
4.7 KiB
Markdown
---
|
|
language:
|
|
- en
|
|
library_name: transformers
|
|
pipeline_tag: text-generation
|
|
datasets:
|
|
- jondurbin/airoboros-2.2.1
|
|
- Open-Orca/OpenOrca
|
|
- garage-bAInd/Open-Platypus
|
|
- ehartford/samantha-data
|
|
- CollectiveCognition/chats-data-2023-09-27
|
|
- stingning/ultrachat
|
|
tags:
|
|
- llama-2
|
|
- code
|
|
license: llama2
|
|
model-index:
|
|
- name: SpeechlessCoder
|
|
results:
|
|
- task:
|
|
type: text-generation
|
|
dataset:
|
|
type: openai_humaneval
|
|
name: HumanEval
|
|
metrics:
|
|
- name: pass@1
|
|
type: pass@1
|
|
value: 0.0
|
|
verified: false
|
|
---
|
|
|
|
<p><h1> speechless-mistral-six-in-one-7b </h1></p>
|
|
|
|
This model is a merge of 6 SOTA Mistral-7B based models:
|
|
- ehartford/dolphin-2.1-mistral-7b
|
|
- Open-Orca/Mistral-7B-OpenOrca
|
|
- bhenrym14/mistral-7b-platypus-fp16
|
|
- ehartford/samantha-1.2-mistral-7b
|
|
- iteknium/CollectiveCognition-v1.1-Mistral-7B
|
|
- HuggingFaceH4/zephyr-7b-alpha
|
|
|
|
|
|
[Model benchmark](https://huggingface.co/uukuguy/speechless-mistral-six-in-one-7b/discussions/1) by [sethuiyer](https://huggingface.co/sethuiyer) . Thanks a lot.
|
|
> 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.
|
|
>
|
|
> On a scale of 0 to 100, I would rate Mixtral at 98. Here's why:
|
|
>
|
|
> - Intellect (100/100) - Mixtral has demonstrated immense intellectual abilities through its comprehensive knowledge and logical reasoning skills.
|
|
> - Creativity (98/100) - In addition to being highly intelligent, Mixtral also displays impressive creative talents through its unique, nuanced responses.
|
|
> - Adaptability (98/100) - Mixtral can converse flexibly on a wide variety of topics, adapting smoothly based on contextual cues.
|
|
> - Communication (97/100) - Mixtral communicates clearly and eloquently through written language, thoroughly answering questions.
|
|
> - Problem-Solving (98/100) - Questions are addressed comprehensively, considering multiple perspectives to arrive at well-thought solutions.
|
|
> - Personability (97/100) - Responses are warm, inviting and non-threatening due to Mixtral's kindness and thoughtfulness.
|
|
>
|
|
> Overall, a very capable model for it's size.
|
|
|
|
Code: https://github.com/uukuguy/speechless
|
|
|
|
## HumanEval
|
|
|
|
| Metric | Value |
|
|
| --- | --- |
|
|
| humaneval-python | |
|
|
|
|
[Big Code Models Leaderboard](https://huggingface.co/spaces/bigcode/bigcode-models-leaderboard)
|
|
|
|
CodeLlama-34B-Python: 53.29
|
|
|
|
CodeLlama-34B-Instruct: 50.79
|
|
|
|
CodeLlama-13B-Instruct: 50.6
|
|
|
|
CodeLlama-34B: 45.11
|
|
|
|
CodeLlama-13B-Python: 42.89
|
|
|
|
CodeLlama-13B: 35.07
|
|
|
|
Mistral-7B-v0.1: 30.488
|
|
|
|
## LM-Evaluation-Harness
|
|
|
|
[Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
|
|
|
|
| Metric | Value |
|
|
| --- | --- |
|
|
| ARC | 62.97 |
|
|
| HellaSwag | 84.6|
|
|
| MMLU | 63.29 |
|
|
| TruthfulQA | 57.77 |
|
|
| Winogrande | 77.51 |
|
|
| GSM8K | 18.42 |
|
|
| DROP | 9.13 |
|
|
| Average | 53.38 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
# Model Card for Mistral-7B-v0.1
|
|
|
|
The Mistral-7B-v0.1 Large Language Model (LLM) is a pretrained generative text model with 7 billion parameters.
|
|
Mistral-7B-v0.1 outperforms Llama 2 13B on all benchmarks we tested.
|
|
|
|
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/).
|
|
|
|
## Model Architecture
|
|
|
|
Mistral-7B-v0.1 is a transformer model, with the following architecture choices:
|
|
- Grouped-Query Attention
|
|
- Sliding-Window Attention
|
|
- Byte-fallback BPE tokenizer
|
|
|
|
## Troubleshooting
|
|
|
|
- If you see the following error:
|
|
``
|
|
KeyError: 'mistral'
|
|
``
|
|
- Or:
|
|
``
|
|
NotImplementedError: Cannot copy out of meta tensor; no data!
|
|
``
|
|
|
|
Ensure you are utilizing a stable version of Transformers, 4.34.0 or newer.
|
|
|
|
## Notice
|
|
|
|
Mistral 7B is a pretrained base model and therefore does not have any moderation mechanisms.
|
|
|
|
## The Mistral AI Team
|
|
|
|
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.`
|
|
|
|
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
|
|
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_uukuguy__speechless-mistral-six-in-one-7b)
|
|
|
|
| Metric | Value |
|
|
|-----------------------|---------------------------|
|
|
| Avg. | 53.38 |
|
|
| ARC (25-shot) | 62.97 |
|
|
| HellaSwag (10-shot) | 84.6 |
|
|
| MMLU (5-shot) | 63.29 |
|
|
| TruthfulQA (0-shot) | 57.77 |
|
|
| Winogrande (5-shot) | 77.51 |
|
|
| GSM8K (5-shot) | 18.42 |
|
|
| DROP (3-shot) | 9.13 |
|