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---
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-6bit
The Model [maxrubin629/DeepHermes-3-Llama-3-8B-Preview-6bit](https://huggingface.co/maxrubin629/DeepHermes-3-Llama-3-8B-Preview-6bit) 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-6bit")
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)
```
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