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---
base_model: NousResearch/Hermes-4.3-36B
language:
- en
library_name: mlx
license: apache-2.0
pipeline_tag: text-generation
tags:
- Bytedance Seed
- instruct
- finetune
- reasoning
- hybrid-mode
- chatml
- function calling
- tool use
- json mode
- structured outputs
- atropos
- dataforge
- long context
- roleplaying
- chat
- 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.
model-index:
- name: Hermes-4.3-ByteDance-Seed-36B
results: []
---
# leonsarmiento/Hermes-4.3-36B-3bit-mlx
This model [leonsarmiento/Hermes-4.3-36B-3bit-mlx](https://huggingface.co/leonsarmiento/Hermes-4.3-36B-3bit-mlx) was
converted to MLX format from [NousResearch/Hermes-4.3-36B](https://huggingface.co/NousResearch/Hermes-4.3-36B)
using mlx-lm version **0.28.3**.
MIXED QUANT: 6-BIT EMBEDDINGS AND PREDICTION LAYERS, 3-BIT EVERYTHING ELSE.
Temperature: 0.6 Top K: 20 Repeat penalty: OFF Min P sampling: OFF Top P sampling: 0.95
SYSTEM PROMPT:
"You are a deep thinking AI, you may use extremely long chains of thought to deeply consider the problem and deliberate with yourself via systematic reasoning processes to help come to a correct solution prior to answering. You should enclose your thoughts and internal monologue inside <think> </think> tags, and then provide your solution or response to the problem."
## Use with mlx
```bash
pip install mlx-lm
```
```python
from mlx_lm import load, generate
model, tokenizer = load("leonsarmiento/Hermes-4.3-36B-3bit-mlx")
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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