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README.md

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+---
+license: other
+license_name: llm-jp-3-172b-instruct3-tou
+license_link: https://huggingface.co/llm-jp/llm-jp-3-172b-instruct3/raw/main/LICENSE
+language:
+- en
+- ja
+programming_language:
+- C
+- C++
+- C#
+- Go
+- Java
+- JavaScript
+- Lua
+- PHP
+- Python
+- Ruby
+- Rust
+- Scala
+- TypeScript
+pipeline_tag: text-generation
+library_name: transformers
+inference: false
+tags:
+- mlx
+base_model: llm-jp/llm-jp-3-172b-instruct3
+---
+
+# schroneko/llm-jp-3-172b-instruct3-Q4-mlx
+
+The Model [schroneko/llm-jp-3-172b-instruct3-Q4-mlx](https://huggingface.co/schroneko/llm-jp-3-172b-instruct3-Q4-mlx) was converted to MLX format from [llm-jp/llm-jp-3-172b-instruct3](https://huggingface.co/llm-jp/llm-jp-3-172b-instruct3) using mlx-lm version **0.20.5**.
+
+## Use with mlx
+
+```bash
+pip install mlx-lm
+```
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("schroneko/llm-jp-3-172b-instruct3-Q4-mlx")
+
+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)
+```