---
base_model: mlx-community/llm-jp-3-1.8b-instruct
language:
- en
- ja
library_name: transformers
license: apache-2.0
pipeline_tag: text-generation
tags:
- mlx
- mlx
programming_language:
- C
- C++
- C#
- Go
- Java
- JavaScript
- Lua
- PHP
- Python
- Ruby
- Rust
- Scala
- TypeScript
inference: false
---

# thr3a/llm-jp-3-1.8b-instruct-mlx

The Model [thr3a/llm-jp-3-1.8b-instruct-mlx](https://huggingface.co/thr3a/llm-jp-3-1.8b-instruct-mlx) was converted to MLX format from [mlx-community/llm-jp-3-1.8b-instruct](https://huggingface.co/mlx-community/llm-jp-3-1.8b-instruct) using mlx-lm version **0.18.2**.

## Use with mlx

```bash
pip install mlx-lm
```

```python
from mlx_lm import load, generate

model, tokenizer = load("thr3a/llm-jp-3-1.8b-instruct-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)
```