Instructions to use Mincofficial/Minico-M1-1105-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Mincofficial/Minico-M1-1105-MLX 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("Mincofficial/Minico-M1-1105-MLX")

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 Mincofficial/Minico-M1-1105-MLX with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "Mincofficial/Minico-M1-1105-MLX"

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "mlx-lm": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "Mincofficial/Minico-M1-1105-MLX"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

MLX LM

How to use Mincofficial/Minico-M1-1105-MLX with MLX LM:

Generate or start a chat session

# Install MLX LM
uv tool install mlx-lm
# Interactive chat REPL
mlx_lm.chat --model "Mincofficial/Minico-M1-1105-MLX"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "Mincofficial/Minico-M1-1105-MLX"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "Mincofficial/Minico-M1-1105-MLX",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

Hermes Agent

How to use Mincofficial/Minico-M1-1105-MLX 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 "Mincofficial/Minico-M1-1105-MLX"

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 Mincofficial/Minico-M1-1105-MLX

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use Mincofficial/Minico-M1-1105-MLX with OpenClaw:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "Mincofficial/Minico-M1-1105-MLX"

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "Mincofficial/Minico-M1-1105-MLX" \
  --custom-provider-id mlx-lm \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Minico M1 1105 MLX

8-bit MLX build of Mincofficial/Minico-M1-1105 for Apple silicon (near-lossless at this size). For full precision, mlx_lm loads the main repo directly: --model Mincofficial/Minico-M1-1105.

pip install mlx-lm
mlx_lm.generate --model Mincofficial/Minico-M1-1105-MLX --prompt "What is 5 + 5 x 5?" --chat-template-config '{"reasoning_effort":"low"}'

Effort levels

Effort	What it does	Max new tokens we use
`off`	No thinking. Answers right away (an empty think block is prefilled).	1024
`low`	A short thought, then the answer.	640
`medium`	A normal thought.	1152
`high` (default)	Longer, more careful reasoning.	2368
`max`	The longest reasoning.	4608

The chat template also accepts aliases (none, minimal, xhigh, and others) and enable_thinking=False, which means off. Without a reasoning_effort, and for unknown values, it uses high (the default since 2026-11-08; it was medium). Recommended sampling: temperature 0.1–0.3, top_k 50, repetition penalty 1.05.

Pick one effort per conversation. Switching the effort, or turning thinking on or off, partway through a chat is not recommended: the model was trained on chats that keep one setting from start to finish. Start a new chat to change it.

License

Minico M1 1105 is a modified version of LiquidAI/LFM2.5-350M and is released under the LFM Open License v1.0 (see LICENSE). The weights were changed by fine-tuning (SFT, DPO, GRPO) and weight merging, as described above. Commercial use is allowed for organisations under the revenue threshold set in the license; read it before using the model commercially.

Built on LFM2.5-350M by Liquid AI. Attribution notices from the base model are kept in LICENSE.

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Safetensors

Model size

0.4B params

Tensor type

U32

BF16

MLX

Hardware compatibility

8-bit

Model tree for Mincofficial/Minico-M1-1105-MLX

Base model

LiquidAI/LFM2.5-350M-Base

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Finetuned

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