[whatmodel.sh](../../README.md) / speechless-coder-ds-6.7b
# speechless-coder-ds-6.7b
uukuguy · released 2023-12 · apache-2.0
**score 48.2** ±0.9 · #406 of 732 · from 3 benchmark results across 1 source
Score within the [LMArena (text)](https://whatmodel.sh/?set=lmarena-text&score=set) comparison set only.
## What it's good at
● marks speechless-coder-ds-6.7b among every model on that task or test, worst to best.
task vs the others rank counts tests
coding ▁▁▁▃▅●█▇▅▄▃▁ #312 of 469 100% 3
coding · #312 of 469 · 100% of its score
Beats [Solar Open 100B (102B-A12B)](solar-open-100b.md), [Qwen3-VL 30B-A3B Instruct](qwen3-vl-30b-a3b-instruct.md), [Qwen3 4B Instruct 2507](qwen3-4b-instruct-2507.md) here, though they rank higher overall. Trails [DeepSeek LLM 67B Chat](deepseek-llm-67b-chat.md), [WizardLM 70B V1.0](wizardlm-70b-v1-0.md), [Yi 1.5 9B Chat](yi-1-5-9b-chat.md) here, though they rank lower overall.
test result vs the others in its run difficulty counts why
HumanEval 71.3% ▁·▁▁▃▄▆●█▃▁▁ beats 60/99 easy · avg 76% 49% sharp · at its level
HumanEval+ 65.9% ▁·▁▁▁▃▄▄▄●▃▁ beats 60/99 easy · avg 70% 42% sharp · at its level
MBPP+ 64.4% ▁···▁▁▂▅▇●▆▂ beats 48/75 easy · avg 66% 8.5% at its level
source results share of the score
EvalPlus / EvalPerf published evaluatio… 3 100% ▇▇▇▇▇▇▇▇▇▇▇▇
prior: pull toward the middle 0% ▇
weighted average = 48.2
Licences: EvalPlus / EvalPerf published evaluation runs ([Apache-2.0](../../licenses/evalplus-published-runs-Apache-2.0.txt))
## How to run it
### llama.cpp (recommended)
1. Install llama.cpp. Homebrew and winget installs name the commands llama-cli and llama-server instead. [Other ways to install](https://github.com/ggml-org/llama.cpp/blob/master/docs/install.md)
```sh
# macOS / Linux
curl -LsSf https://llama.app/install.sh | sh
# Windows
irm https://llama.app/install.ps1 | iex
```
2. Run speechless-coder-ds-6.7b (Q4_K_M, needs ~4.1 GB, from [huggingface.co/uukuguy](https://huggingface.co/uukuguy/speechless-coder-ds-6.7b/tree/c813a5268c6dfe267a720ad3b51773f1ab0feb59))
```sh
llama cli -hf uukuguy/speechless-coder-ds-6.7b:Q4_K_M
```
3. Or start a local server and open the address it prints (http://localhost:9931)
```sh
llama serve -hf uukuguy/speechless-coder-ds-6.7b:Q4_K_M
```
Other versions: Q8_0 (~7.2 GB) `llama cli -hf uukuguy/speechless-coder-ds-6.7b:Q8_0`
### LM Studio
1. Install LM Studio. Open the app once before using the lms command. [Download it (macOS / Windows / Linux)](https://lmstudio.ai/download)
2. Run speechless-coder-ds-6.7b (Q4_K_M, needs ~4.1 GB, from [huggingface.co/uukuguy](https://huggingface.co/uukuguy/speechless-coder-ds-6.7b/tree/c813a5268c6dfe267a720ad3b51773f1ab0feb59))
```sh
lms get https://huggingface.co/uukuguy/speechless-coder-ds-6.7b@Q4_K_M -y
```
3. Then run lms ls to see its name, and lms chat followed by that name
Other versions: Q8_0 (~7.2 GB) `lms get https://huggingface.co/uukuguy/speechless-coder-ds-6.7b@Q8_0 -y`
### Ollama
1. Install Ollama. [Download it (macOS / Windows)](https://ollama.com/download)
```sh
# Linux
curl -fsSL https://ollama.com/install.sh | sh
```
2. Run speechless-coder-ds-6.7b (Q4_K_M, needs ~4.1 GB, from [huggingface.co/uukuguy](https://huggingface.co/uukuguy/speechless-coder-ds-6.7b/tree/c813a5268c6dfe267a720ad3b51773f1ab0feb59))
```sh
ollama run hf.co/uukuguy/speechless-coder-ds-6.7b:Q4_K_M
```
Other versions: Q8_0 (~7.2 GB) `ollama run hf.co/uukuguy/speechless-coder-ds-6.7b:Q8_0`
### Other ways to run it
1. Run it as published (fp16, needs ~13.48 GB, from [huggingface.co/uukuguy](https://huggingface.co/uukuguy/speechless-coder-ds-6.7b/tree/c813a5268c6dfe267a720ad3b51773f1ab0feb59))
```sh
uv run --with torch --with 'transformers<5' --with accelerate python -c "from transformers import pipeline; print(pipeline('text-generation', model='uukuguy/speechless-coder-ds-6.7b', 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-coder-ds-6.7b)
[interactive version](https://whatmodel.sh/model/speechless-coder-ds-6-7b) · [JSON](https://whatmodel.sh/api?format=json&all=1)