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---
license: mit
library_name: mlx
base_model: huihui-ai/DeepSeek-R1-0528-Qwen3-8B-abliterated
tags:
- chat
- abliterated
- uncensored
- mlx
extra_gated_prompt: '**Usage Warnings**
“**Risk of Sensitive or Controversial Outputs**“: This models safety filtering
has been significantly reduced, potentially generating sensitive, controversial,
or inappropriate content. Users should exercise caution and rigorously review generated
outputs.
“**Not Suitable for All Audiences**:“ Due to limited content filtering, the models
outputs may be inappropriate for public settings, underage users, or applications
requiring high security.
“**Legal and Ethical Responsibilities**“: Users must ensure their usage complies
with local laws and ethical standards. Generated content may carry legal or ethical
risks, and users are solely responsible for any consequences.
“**Research and Experimental Use**“: It is recommended to use this model for research,
testing, or controlled environments, avoiding direct use in production or public-facing
commercial applications.
“**Monitoring and Review Recommendations**“: Users are strongly advised to monitor
model outputs in real-time and conduct manual reviews when necessary to prevent
the dissemination of inappropriate content.
“**No Default Safety Guarantees**“: Unlike standard models, this model has not undergone
rigorous safety optimization. huihui.ai bears no responsibility for any consequences
arising from its use.'
pipeline_tag: text-generation
---
# SnowFlash383935/DeepSeek-R1-0528-Qwen3-8B-abliterated-mlx
This model [SnowFlash383935/DeepSeek-R1-0528-Qwen3-8B-abliterated-mlx](https://huggingface.co/SnowFlash383935/DeepSeek-R1-0528-Qwen3-8B-abliterated-mlx) was
converted to MLX format from [huihui-ai/DeepSeek-R1-0528-Qwen3-8B-abliterated](https://huggingface.co/huihui-ai/DeepSeek-R1-0528-Qwen3-8B-abliterated)
using mlx-lm version **0.25.2**.
## Use with mlx
```bash
pip install mlx-lm
```
```python
from mlx_lm import load, generate
model, tokenizer = load("SnowFlash383935/DeepSeek-R1-0528-Qwen3-8B-abliterated-mlx")
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)
```