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---
language:
- en
license: llama3
tags:
- Llama-3.1
- unsloth
- instruct
- finetune
- reasoning
- hybrid-mode
- chatml
- function calling
- tool use
- json mode
- structured outputs
- atropos
- dataforge
- long context
- roleplaying
- chat
- mlx
- mlx-my-repo
base_model: unsloth/Hermes-4-405B
library_name: transformers
widget:
- example_title: Hermes 4
  messages:
  - role: system
    content: You are Hermes 4, a capable, neutrally-aligned assistant. Prefer concise,
      correct answers.
  - role: user
    content: Explain the difference between BFS and DFS to a new CS student.
model-index:
- name: Hermes-4-Llama-3.1-405B
  results: []
---

# mrtoots/unsloth-Hermes-4-405B-mlx-3Bit

The Model [mrtoots/unsloth-Hermes-4-405B-mlx-3Bit](https://huggingface.co/mrtoots/unsloth-Hermes-4-405B-mlx-3Bit) was converted to MLX format from [unsloth/Hermes-4-405B](https://huggingface.co/unsloth/Hermes-4-405B) using mlx-lm version **0.26.4**.



## Toots' Note:
This model was converted and quantized utilizing unsloth's version of Hermes-4-405B. Should include the chat template fixes.

Please follow and support [unsloth's work](https://huggingface.co/unsloth) if you like it!

🦛 <span style="color:#800080">If you want a free consulting session, </span>[fill out this form](https://forms.gle/xM9gw1urhypC4bWS6) <span style="color:#800080">to get in touch!</span> 🤗



## Use with mlx

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

```python
from mlx_lm import load, generate

model, tokenizer = load("mrtoots/Hermes-4-405B-mlx-3Bit")

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)
```