base_model: mlx-community/llm-jp-3-3.7b-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-3-3.7b-instruct-mlx | |
The Model [thr3a/llm-jp-3-3.7b-instruct-mlx](https://huggingface.co/thr3a/llm-jp-3-3.7b-instruct-mlx) was converted to MLX format from [mlx-community/llm-jp-3-3.7b-instruct](https://huggingface.co/mlx-community/llm-jp-3-3.7b-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-3-3.7b-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) | |
``` | |