---
datasets:
- TeichAI/claude-4.5-opus-high-reasoning-250x
base_model: TeichAI/Nemotron-Orchestrator-8B-Claude-4.5-Opus-Distill
library_name: mlx
tags:
- mlx
pipeline_tag: text-generation
---

# Nemotron-Orchestrator-8B-Claude-4.5-Opus-Distill-qx86-hi-mlx

This model [Nemotron-Orchestrator-8B-Claude-4.5-Opus-Distill-qx86-hi-mlx](https://huggingface.co/Nemotron-Orchestrator-8B-Claude-4.5-Opus-Distill-qx86-hi-mlx) was
converted to MLX format from [TeichAI/Nemotron-Orchestrator-8B-Claude-4.5-Opus-Distill](https://huggingface.co/TeichAI/Nemotron-Orchestrator-8B-Claude-4.5-Opus-Distill)
using mlx-lm version **0.29.0**.

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("Nemotron-Orchestrator-8B-Claude-4.5-Opus-Distill-qx86-hi-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)
```