---
language:
- en
license: llama3
tags:
- Llama-3
- instruct
- finetune
- chatml
- gpt4
- synthetic data
- distillation
- function calling
- json mode
- axolotl
- roleplaying
- chat
- reasoning
- r1
- vllm
- mlx
- mlx-my-repo
base_model: NousResearch/DeepHermes-3-Llama-3-8B-Preview
widget:
- example_title: Hermes 3
  messages:
  - role: system
    content: You are a sentient, superintelligent artificial general intelligence,
      here to teach and assist me.
  - role: user
    content: What is the meaning of life?
library_name: transformers
model-index:
- name: DeepHermes-3-Llama-3.1-8B
  results: []
---

# maxrubin629/DeepHermes-3-Llama-3-8B-Preview-Q2-mlx

The Model [maxrubin629/DeepHermes-3-Llama-3-8B-Preview-Q2-mlx](https://huggingface.co/maxrubin629/DeepHermes-3-Llama-3-8B-Preview-Q2-mlx) was converted to MLX format from [NousResearch/DeepHermes-3-Llama-3-8B-Preview](https://huggingface.co/NousResearch/DeepHermes-3-Llama-3-8B-Preview) using mlx-lm version **0.20.5**.

## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("maxrubin629/DeepHermes-3-Llama-3-8B-Preview-Q2-mlx")

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)
```