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README.md

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+---
+thumbnail: https://cdn-uploads.huggingface.co/production/uploads/66c26b6fb01b19d8c3c2467b/jg2NWmCUfPyzizm2USjMt.jpeg
+datasets:
+- NewEden/Orion-LIT
+- NewEden/Orion-Asstr-Stories-16K
+- Mielikki/Erebus-87k
+- PocketDoc/Dans-MemoryCore-CoreCurriculum-Small
+- Nitral-AI/ARES-ShareGPT
+- Gryphe/Sonnet3.5-SlimOrcaDedupCleaned-20k
+- NewEden/Claude-Instruct-2.7K
+- NewEden/Claude-Instruct-5K
+base_model: Delta-Vector/Hamanasu-15B-Instruct
+tags:
+- phi
+- roleplay
+- finetune
+- storywriting
+- mlx
+- mlx-my-repo
+---
+
+# aimeri/Hamanasu-15B-Instruct-6bit
+
+The Model [aimeri/Hamanasu-15B-Instruct-6bit](https://huggingface.co/aimeri/Hamanasu-15B-Instruct-6bit) was converted to MLX format from [Delta-Vector/Hamanasu-15B-Instruct](https://huggingface.co/Delta-Vector/Hamanasu-15B-Instruct) 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("aimeri/Hamanasu-15B-Instruct-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)
+```