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README.md

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+---
+base_model: NousResearch/Hermes-4-70B
+language:
+- en
+library_name: transformers
+license: llama3
+pipeline_tag: text-generation
+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
+- mlx-my-repo
+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-3.1-70B
+  results: []
+---
+
+# Wwayu/Hermes-4-70B-mlx-4Bit
+
+The Model [Wwayu/Hermes-4-70B-mlx-4Bit](https://huggingface.co/Wwayu/Hermes-4-70B-mlx-4Bit) was converted to MLX format from [NousResearch/Hermes-4-70B](https://huggingface.co/NousResearch/Hermes-4-70B) using mlx-lm version **0.26.4**.
+
+## Use with mlx
+
+```bash
+pip install mlx-lm
+```
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("Wwayu/Hermes-4-70B-mlx-4Bit")
+
+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)
+```