---
license: apache-2.0
pipeline_tag: text-generation
library_name: transformers
tags:
- vllm
- mlx
- gpt
- gpt-oss
- gpt-oss-safeguard
- oss
- openai
base_model: openai/gpt-oss-safeguard-20b
base_model_relation: quantized
---

# SiddhJagani/gpt-oss-safeguard-20b-mlx-2Bit

The Model [SiddhJagani/gpt-oss-safeguard-20b-mlx-2Bit](https://huggingface.co/SiddhJagani/gpt-oss-safeguard-20b-mlx-Q2) was converted to MLX format from [openai/gpt-oss-safeguard-20b](https://huggingface.co/openai/gpt-oss-safeguard-20b) using mlx-lm version **0.28.2**.

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("SiddhJagani/gpt-oss-safeguard-20b-mlx-Q2")

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
    )
    # Force our custom assistant marker
    prompt = force_generation_prompt(prompt)

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