---
title: Arcee-Blitz-8bit
canonical_url: "https://www.modelscope.cn/models/mlx-community/Arcee-Blitz-8bit"
md_url: "https://www.modelscope.cn/models/mlx-community/Arcee-Blitz-8bit.md"
repository: mlx-community/Arcee-Blitz-8bit
last_updated: 2025-06-04
license: apache-2.0
pipeline_tag: text-generation
tasks:
  - text-generation
model_type:
  - mistral
architectures:
  - MistralForCausalLM
base_model:
  - arcee-ai/Arcee-Blitz
base_model_relation: quantized
parameters: 6.6B
tensor_type:
  - BF16
  - U32
library_name:
  - mlx
  - safetensors
  - pytorch
frameworks:
  - pytorch
inference_backends:
  - "deploy_task text/emb"
  - "lmdeploy 0.9.1"
  - "lmdeploy_turbomind 0.9.1"
  - "sglang 0.5.2"
  - "vllm 0.9.2"
downloads: 604
stars: 0
tags:
  - mlx
---

# Arcee-Blitz-8bit

> Arcee-Blitz-8bit - mlx-community 在 ModelScope 开源的模型。mlx-community/Arcee-Blitz-8bit

mlx-community/Arcee-Blitz-8bit 是 ModelScope 魔搭社区上的 6.6B 参数text-generation模型，采用 apache-2.0 许可，基于 arcee-ai/Arcee-Blitz 构建，可用 deploy_task text/emb、lmdeploy 0.9.1、lmdeploy_turbomind 0.9.1 部署。

- **Repository**: mlx-community/Arcee-Blitz-8bit
- **License**: apache-2.0
- **Tasks**: text-generation
- **Parameters**: 6.6B
- **Base model**: arcee-ai/Arcee-Blitz
- **Inference backends**: deploy_task text/emb, lmdeploy 0.9.1, lmdeploy_turbomind 0.9.1, sglang 0.5.2, vllm 0.9.2
- **Tags**: mlx
- **Downloads**: 604
- **Stars**: 0
- **Last updated**: 2025-06-04

Source: https://www.modelscope.cn/models/mlx-community/Arcee-Blitz-8bit

---

# mlx-community/Arcee-Blitz-8bit

This model [mlx-community/Arcee-Blitz-8bit](https://huggingface.co/mlx-community/Arcee-Blitz-8bit) was
converted to MLX format from [arcee-ai/Arcee-Blitz](https://huggingface.co/arcee-ai/Arcee-Blitz)
using mlx-lm version **0.25.0**.

## Use with mlx

```bash
pip install mlx-lm
```

```python
from mlx_lm import load, generate

model, tokenizer = load("mlx-community/Arcee-Blitz-8bit")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)
```