---
base_model: TeichAI/Nemotron-Cascade-8B-Thinking-Claude-4.5-Opus-High-Reasoning-Distill
tags:
- text-generation-inference
- transformers
- unsloth
- mlx
- nvidia
- cascade
- lm-studio
license: apache-2.0
language:
- en
datasets:
- TeichAI/claude-4.5-opus-high-reasoning-250x
---

# SiddhJagani/Nemotron-Cascade-8B-Thinking-Claude-4.5-Opus-High-Reasoning-Distill-mlx-Q6

The Model [SiddhJagani/Nemotron-Cascade-8B-Thinking-Claude-4.5-Opus-High-Reasoning-Distill-mlx-Q6](https://huggingface.co/SiddhJagani/Nemotron-Cascade-8B-Thinking-Claude-4.5-Opus-High-Reasoning-Distill-mlx-Q6) was converted to MLX format from [TeichAI/Nemotron-Cascade-8B-Thinking-Claude-4.5-Opus-High-Reasoning-Distill](https://huggingface.co/TeichAI/Nemotron-Cascade-8B-Thinking-Claude-4.5-Opus-High-Reasoning-Distill) using mlx-lm version **0.28.3**.

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("SiddhJagani/Nemotron-Cascade-8B-Thinking-Claude-4.5-Opus-High-Reasoning-Distill-mlx-Q6")

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)
```