Instructions to use mlx-community/MiniMax-M2.7-nvfp4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/MiniMax-M2.7-nvfp4 with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("mlx-community/MiniMax-M2.7-nvfp4") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use mlx-community/MiniMax-M2.7-nvfp4 with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "mlx-community/MiniMax-M2.7-nvfp4" --prompt "Once upon a time"
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pipeline_tag: text-generation
license: other
license_name: modified-mit
license_link: https://github.com/MiniMax-AI/MiniMax-M2.7/blob/main/LICENSE
library_name: mlx
tags:
- mlx
base_model: MiniMaxAI/MiniMax-M2.7
---
# mlx-community/MiniMax-M2.7-nvfp4
This model [mlx-community/MiniMax-M2.7-nvfp4](https://huggingface.co/mlx-community/MiniMax-M2.7-nvfp4) was
converted to MLX format from [MiniMaxAI/MiniMax-M2.7](https://huggingface.co/MiniMaxAI/MiniMax-M2.7)
using mlx-lm version **0.31.2**.
## Use with mlx
```bash
pip install mlx-lm
```
```python
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/MiniMax-M2.7-nvfp4")
prompt = "hello"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True, return_dict=False,
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)
```
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