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Josiefied-Qwen2.5-0.5B-Inst…/README.md
ModelHub XC 2892e2a7ac 初始化项目,由ModelHub XC社区提供模型
Model: mlx-community/Josiefied-Qwen2.5-0.5B-Instruct-abliterated-v1-float32
Source: Original Platform
2026-05-26 16:38:13 +08:00

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---
base_model: Goekdeniz-Guelmez/Josiefied-Qwen2.5-0.5B-Instruct-abliterated-v1
language:
- en
- de
license: apache-2.0
pipeline_tag: text-generation
tags:
- chat
- mlx
---
# mlx-community/Josiefied-Qwen2.5-0.5B-Instruct-abliterated-v1-float32
The Model [mlx-community/Josiefied-Qwen2.5-0.5B-Instruct-abliterated-v1-float32](https://huggingface.co/mlx-community/Josiefied-Qwen2.5-0.5B-Instruct-abliterated-v1-float32) was converted to MLX format from [Goekdeniz-Guelmez/Josiefied-Qwen2.5-0.5B-Instruct-abliterated-v1](https://huggingface.co/Goekdeniz-Guelmez/Josiefied-Qwen2.5-0.5B-Instruct-abliterated-v1) using mlx-lm version **0.18.2**.
## Use with mlx
```bash
pip install mlx-lm
```
```python
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/Josiefied-Qwen2.5-0.5B-Instruct-abliterated-v1-float32")
prompt="hello"
if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)
```