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---
language:
- en
license: llama3
tags:
- Llama-3.1
- instruct
- finetune
- reasoning
- hybrid-mode
- chatml
- function calling
- tool use
- json mode
- structured outputs
- atropos
- dataforge
- long context
- roleplaying
- chat
- mlx
base_model: NousResearch/Hermes-4-70B
library_name: mlx
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.
pipeline_tag: text-generation
model-index:
- name: Hermes-4-Llama-3.1-70B
results: []
---
# mlx-community/Hermes-4-70B-4bit
This model [mlx-community/Hermes-4-70B-4bit](https://huggingface.co/mlx-community/Hermes-4-70B-4bit) was
converted to MLX format from [NousResearch/Hermes-4-70B](https://huggingface.co/NousResearch/Hermes-4-70B)
using mlx-lm version **0.26.3**.
## Use with mlx
```bash
pip install mlx-lm
```
```python
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/Hermes-4-70B-4bit")
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)
```
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