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README.md

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+---
+language:
+- en
+license: apache-2.0
+tags:
+- Mistral-Small
+- 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-Mistral-24B-Preview
+widget:
+- example_title: DeepHermes 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-Mistral-24B-Preview
+  results: []
+---
+
+# Jarrodbarnes/DeepHermes-3-Mistral-24B-Preview-mlx-fp16
+
+The Model [Jarrodbarnes/DeepHermes-3-Mistral-24B-Preview-mlx-fp16](https://huggingface.co/Jarrodbarnes/DeepHermes-3-Mistral-24B-Preview-mlx-fp16) was converted to MLX format from [NousResearch/DeepHermes-3-Mistral-24B-Preview](https://huggingface.co/NousResearch/DeepHermes-3-Mistral-24B-Preview) using mlx-lm version **0.21.5**.
+
+## Use with mlx
+
+```bash
+pip install mlx-lm
+```
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("Jarrodbarnes/DeepHermes-3-Mistral-24B-Preview-mlx-fp16")
+
+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)
+```