[whatmodel.sh](../../README.md) / speechless-code-mistral-7b-v1.0 # speechless-code-mistral-7b-v1.0 uukuguy · released 2023-10 · apache-2.0 **score 40.3** ±0.8 · #560 of 732 · from 4 benchmark results across 2 sources Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only. ## What it's good at _{● marks speechless-code-mistral-7b-v1.0 among every model on that task or test, worst to best.}

task    vs the others         rank  counts  tests
coding  ▁▁▁▃●▇█▇▅▄▃▁   #395 of 469     98%      3

coding · #395 of 469 · 98% of its score

Beats [DeepSeek R1 Distill Qwen 7B](deepseek-r1-distill-qwen-7b.md), [Qwen3.5 2B](qwen3-5-2b.md), [DeepSeek R1 Distill Llama 8B](deepseek-r1-distill-llama-8b.md) here, though they rank higher overall. Trails [Qwen2.5 1.5B Instruct](qwen2-5-1-5b.md), [WizardLM 13B V1.2](wizardlm-13b-v1-2.md), [Falcon3 3B Instruct](falcon3-3b.md) here, though they rank lower overall.

test        result  vs the others in its run  difficulty      counts  why
HumanEval    48.2%  ▁·▁▁▃▄●▅█▃▁▁ beats 33/99  easy · avg 76%     51%  sharp · at its level
HumanEval+   41.5%  ▁·▁▁▁▃▄●▄█▃▁ beats 31/99  easy · avg 70%     39%  sharp · at its level
MBPP+        48.7%  ▁···▁▁▂●▇█▆▂ beats 18/75  easy · avg 66%    7.8%  at its level

other tests (1)

test                                result  vs the others in its run    difficulty        counts  why
Open PT-LLM Leaderboard average (…   64.4%  ▃▁▁▁▁▁▁▁▂●▅▁ beats 110/276  medium · avg 72%    1.5%  at its level · noisy

## How the score was worked out Each result implies a score on its own, after adjusting for how hard that test is and who ran it. The model's score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its *counts* column above; here it is added up by who ran the tests. [Method](../method.md)

source                                    results  share of the score
EvalPlus / EvalPerf published evaluatio…        3   98% ▇▇▇▇▇▇▇▇▇▇▇▇
Open Portuguese LLM Leaderboard                 1    2% ▇
prior: pull toward the middle                        0% ▇
weighted average                                   = 40.3

_{Licences: EvalPlus / EvalPerf published evaluation runs ([Apache-2.0](../../licenses/evalplus-published-runs-Apache-2.0.txt)) · Open Portuguese LLM Leaderboard ([Apache-2.0](../../licenses/hf-leaderboard-spaces-Apache-2.0.txt))} ## How to run it ### Other ways to run it 1. Run it as published (fp16, needs ~14.48 GB, from [huggingface.co/uukuguy](https://huggingface.co/uukuguy/speechless-code-mistral-7b-v1.0/tree/1862e0a712efc6002112e9c1235a197d58419b37)) ```sh uv run --with torch --with 'transformers<5' --with accelerate python -c "from transformers import pipeline; print(pipeline('text-generation', model='uukuguy/speechless-code-mistral-7b-v1.0', torch_dtype='auto', device_map='auto')('Once upon a time', max_new_tokens=40)[0]['generated_text'])" ``` Model repository and documentation: [huggingface.co/uukuguy](https://huggingface.co/uukuguy/speechless-code-mistral-7b-v1.0) [interactive version](https://whatmodel.sh/model/speechless-code-mistral-7b-v1-0) · [JSON](https://whatmodel.sh/api?format=json&all=1)