[whatmodel.sh](../../README.md) / Qwen-7B-Chat
# Qwen-7B-Chat
Alibaba · released 2023-08 · 7.72B params · other (tongyi-qianwen-license-agreement)
**score 32.1** ±1.0 · #649 of 732 · from 11 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 Qwen-7B-Chat among every model on that task or test, worst to best.
other tests (11)
test result vs the others in its run difficulty counts why
ARC Challenge 46.7% ▁·▁··▁▁▇▂█●▃ beats 22/26 easy · avg 82% 51% sharp · at its level
WinoGrande 68.6% ▁····▁··▁▂●▄ beats 20/26 easy · avg 86% 11% at its level
BoolQ 71.7% ▂▃▂▅▆▂▅●█▂▂▂ beats 16/26 easy · avg 88% 8.0% at its level
HellaSwag 85.0% ▃···▁▇▅█▇▃●▁ beats 25/26 very easy · avg 91% 5.4% at its level
ARC Easy 64.5% ▁▁·▁▁▄▅●█▅▁▃ beats 12/26 easy · avg 85% 5.3% blunt · at its level
OpenBookQA 35.6% █·▁▁▃·▁▃▅▇▃● beats 25/26 hard · avg 49% 4.3% typical
SciQ 90.7% ▁·▁·▁·▃●▃█▄▁ beats 9/26 very easy · avg 97% 4.0% blunt
PIQA 78.7% ▁·▁··▁▁▃█▅●▂ beats 20/26 easy · avg 87% 3.9% blunt · at its level
Social IQA 47.0% ▁···▁▃█▁▁●·▁ beats 24/26 hard · avg 56% 2.4% blunt
LAMBADA (OpenAI version), last-wo… 65.5% ▁··▂▁▁▁●▆█▅▃ beats 7/26 very easy · avg 86% 2.3% blunt · at its level
Open PT-LLM Leaderboard average (… 59.9% ▃▁▁▁▁▁▁▁●█▅▁ beats 89/276 medium · avg 72% 1.8% noisy
source results share of the score
Stability AI 10 98% ▇▇▇▇▇▇▇▇▇▇▇▇
Open Portuguese LLM Leaderboard 1 2% ▇
prior: pull toward the middle 0% ▇
weighted average = 32.1
Licences: Stability AI ([Apache-2.0](../../licenses/stablelm-original-eval-json-Apache-2.0.txt)) · Open Portuguese LLM Leaderboard ([Apache-2.0](../../licenses/hf-leaderboard-spaces-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 Qwen-7B-Chat (Q4_K_M, needs ~4.9 GB, from [huggingface.co/mradermacher](https://huggingface.co/mradermacher/Qwen-7B-Chat-GGUF/tree/69d68724e3d87914b0a4ce7400aec996a92b130a))
```sh
llama cli -hf mradermacher/Qwen-7B-Chat-GGUF:Q4_K_M
```
3. Or start a local server and open the address it prints (http://localhost:9931)
```sh
llama serve -hf mradermacher/Qwen-7B-Chat-GGUF:Q4_K_M
```
Other versions: Q8_0 (~8.2 GB) `llama cli -hf mradermacher/Qwen-7B-Chat-GGUF: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 Qwen-7B-Chat (Q4_K_M, needs ~4.9 GB, from [huggingface.co/mradermacher](https://huggingface.co/mradermacher/Qwen-7B-Chat-GGUF/tree/69d68724e3d87914b0a4ce7400aec996a92b130a))
```sh
lms get https://huggingface.co/mradermacher/Qwen-7B-Chat-GGUF@Q4_K_M -y
```
3. Then run lms ls to see its name, and lms chat followed by that name
Other versions: Q8_0 (~8.2 GB) `lms get https://huggingface.co/mradermacher/Qwen-7B-Chat-GGUF@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 Qwen-7B-Chat (Q4_K_M, needs ~4.9 GB, from [huggingface.co/mradermacher](https://huggingface.co/mradermacher/Qwen-7B-Chat-GGUF/tree/69d68724e3d87914b0a4ce7400aec996a92b130a))
```sh
ollama run hf.co/mradermacher/Qwen-7B-Chat-GGUF:Q4_K_M
```
Other versions: Q8_0 (~8.2 GB) `ollama run hf.co/mradermacher/Qwen-7B-Chat-GGUF:Q8_0`
### Other ways to run it
1. Run it as published (BF16, needs ~15.44 GB, from [huggingface.co/Qwen](https://huggingface.co/Qwen/Qwen-7B-Chat/tree/93a65d34827a3cc269b727e67004743b723e2f83))
```sh
uv run --with torch --with 'transformers<5' --with accelerate python -c "from transformers import pipeline; print(pipeline('text-generation', model='Qwen/Qwen-7B-Chat', torch_dtype='auto', device_map='auto', trust_remote_code=True)('Once upon a time', max_new_tokens=40)[0]['generated_text'])"
```
Model repository and documentation: [huggingface.co/Qwen](https://huggingface.co/Qwen/Qwen-7B-Chat)
[interactive version](https://whatmodel.sh/model/qwen-7b-chat) · [JSON](https://whatmodel.sh/api?format=json&all=1)