Instructions to use MimiTechAI/mimi-pro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use MimiTechAI/mimi-pro with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="MimiTechAI/mimi-pro",
	filename="mimi-qwen3-4b-q4km.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use MimiTechAI/mimi-pro with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf MimiTechAI/mimi-pro
# Run inference directly in the terminal:
llama-cli -hf MimiTechAI/mimi-pro

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf MimiTechAI/mimi-pro
# Run inference directly in the terminal:
llama-cli -hf MimiTechAI/mimi-pro

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf MimiTechAI/mimi-pro
# Run inference directly in the terminal:
./llama-cli -hf MimiTechAI/mimi-pro

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf MimiTechAI/mimi-pro
# Run inference directly in the terminal:
./build/bin/llama-cli -hf MimiTechAI/mimi-pro

Use Docker

docker model run hf.co/MimiTechAI/mimi-pro

LM Studio
Jan

vLLM

How to use MimiTechAI/mimi-pro with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "MimiTechAI/mimi-pro"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "MimiTechAI/mimi-pro",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/MimiTechAI/mimi-pro

Ollama
How to use MimiTechAI/mimi-pro with Ollama:
```
ollama run hf.co/MimiTechAI/mimi-pro
```

Unsloth Studio new

How to use MimiTechAI/mimi-pro with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for MimiTechAI/mimi-pro to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for MimiTechAI/mimi-pro to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for MimiTechAI/mimi-pro to start chatting

Pi new

How to use MimiTechAI/mimi-pro with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf MimiTechAI/mimi-pro

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "MimiTechAI/mimi-pro"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use MimiTechAI/mimi-pro with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf MimiTechAI/mimi-pro

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 MimiTechAI/mimi-pro

Run Hermes

hermes

Docker Model Runner
How to use MimiTechAI/mimi-pro with Docker Model Runner:
```
docker model run hf.co/MimiTechAI/mimi-pro
```

Lemonade

How to use MimiTechAI/mimi-pro with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull MimiTechAI/mimi-pro

Run and chat with the model

lemonade run user.mimi-pro-{{QUANT_TAG}}

List all available models

lemonade list

MimiTechAI commited on Mar 3

Commit

32b5a29

verified ·

1 Parent(s): b352940

Upload adapter/adapter_config.json with huggingface_hub

Browse files

Files changed (1) hide show

adapter/adapter_config.json +46 -0

adapter/adapter_config.json ADDED Viewed

	@@ -0,0 +1,46 @@

+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": null,
+  "base_model_name_or_path": "Qwen/Qwen3-4B",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 128,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.1",
+  "qalora_group_size": 16,
+  "r": 64,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "gate_proj",
+    "q_proj",
+    "o_proj",
+    "up_proj",
+    "v_proj",
+    "down_proj",
+    "k_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}