Instructions to use mlx-community/MiMo-7B-SFT-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mlx-community/MiMo-7B-SFT-4bit with MLX:

# Make sure mlx-lm is installed
# pip install --upgrade mlx-lm

# Generate text with mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("mlx-community/MiMo-7B-SFT-4bit")

prompt = "Write a story about Einstein"
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
    messages, add_generation_prompt=True
)

text = generate(model, tokenizer, prompt=prompt, verbose=True)

Notebooks
Google Colab
Kaggle
Local Apps Settings
LM Studio

How to use mlx-community/MiMo-7B-SFT-4bit with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "mlx-community/MiMo-7B-SFT-4bit"

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "mlx-lm": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "mlx-community/MiMo-7B-SFT-4bit"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use mlx-community/MiMo-7B-SFT-4bit with Hermes Agent:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "mlx-community/MiMo-7B-SFT-4bit"

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default mlx-community/MiMo-7B-SFT-4bit

Run Hermes

hermes

MLX LM

How to use mlx-community/MiMo-7B-SFT-4bit with MLX LM:

Generate or start a chat session

# Install MLX LM
uv tool install mlx-lm
# Interactive chat REPL
mlx_lm.chat --model "mlx-community/MiMo-7B-SFT-4bit"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "mlx-community/MiMo-7B-SFT-4bit"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "mlx-community/MiMo-7B-SFT-4bit",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

MiMo-7B-SFT-4bit

File size: 1,161 Bytes

31b3e7c

{
    "architectures": [
        "MiMoForCausalLM"
    ],
    "attention_bias": true,
    "attention_dropout": 0.0,
    "auto_map": {
        "AutoConfig": "configuration_mimo.MiMoConfig",
        "AutoModel": "modeling_mimo.MiMoModel",
        "AutoModelForCausalLM": "modeling_mimo.MiMoForCausalLM"
    },
    "bos_token_id": 151643,
    "eos_token_id": 151645,
    "head_dim": 128,
    "hidden_act": "silu",
    "hidden_size": 4096,
    "initializer_range": 0.02,
    "intermediate_size": 11008,
    "max_position_embeddings": 32768,
    "max_window_layers": 32,
    "model_type": "mimo",
    "num_attention_heads": 32,
    "num_hidden_layers": 36,
    "num_key_value_heads": 8,
    "num_nextn_predict_layers": 1,
    "quantization": {
        "group_size": 64,
        "bits": 4
    },
    "quantization_config": {
        "group_size": 64,
        "bits": 4
    },
    "rms_norm_eps": 1e-05,
    "rope_theta": 640000,
    "sliding_window": 32768,
    "tie_word_embeddings": false,
    "torch_dtype": "bfloat16",
    "transformers_version": "4.40.1",
    "use_cache": true,
    "use_mrope": false,
    "use_sliding_window": false,
    "vocab_size": 151680
}