Instructions to use Goldkoron/MiniMax-M2.7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Goldkoron/MiniMax-M2.7 with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Goldkoron/MiniMax-M2.7",
	filename="MiniMax-M2.7-K_G_2.50.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use Goldkoron/MiniMax-M2.7 with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Goldkoron/MiniMax-M2.7
# Run inference directly in the terminal:
llama-cli -hf Goldkoron/MiniMax-M2.7

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Goldkoron/MiniMax-M2.7
# Run inference directly in the terminal:
llama-cli -hf Goldkoron/MiniMax-M2.7

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 Goldkoron/MiniMax-M2.7
# Run inference directly in the terminal:
./llama-cli -hf Goldkoron/MiniMax-M2.7

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 Goldkoron/MiniMax-M2.7
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Goldkoron/MiniMax-M2.7

Use Docker

docker model run hf.co/Goldkoron/MiniMax-M2.7

LM Studio
Jan
Ollama
How to use Goldkoron/MiniMax-M2.7 with Ollama:
```
ollama run hf.co/Goldkoron/MiniMax-M2.7
```

Unsloth Studio new

How to use Goldkoron/MiniMax-M2.7 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 Goldkoron/MiniMax-M2.7 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 Goldkoron/MiniMax-M2.7 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Goldkoron/MiniMax-M2.7 to start chatting

Pi new

How to use Goldkoron/MiniMax-M2.7 with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf Goldkoron/MiniMax-M2.7

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": "Goldkoron/MiniMax-M2.7"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use Goldkoron/MiniMax-M2.7 with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf Goldkoron/MiniMax-M2.7

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 Goldkoron/MiniMax-M2.7

Run Hermes

hermes

Docker Model Runner
How to use Goldkoron/MiniMax-M2.7 with Docker Model Runner:
```
docker model run hf.co/Goldkoron/MiniMax-M2.7
```

Lemonade

How to use Goldkoron/MiniMax-M2.7 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Goldkoron/MiniMax-M2.7

Run and chat with the model

lemonade run user.MiniMax-M2.7-{{QUANT_TAG}}

List all available models

lemonade list

Goldkoron commited on Apr 13

Commit

68bd47e

verified ·

1 Parent(s): b68e221

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README.md CHANGED Viewed

@@ -18,13 +18,12 @@ Quantizations of [MiniMax-M2.7](https://huggingface.co/MiniMaxAI/MiniMax-M2.7) u
 | Quant | Size | BPW | Mean KLD | Same Top P |
 |-------|------|-----|----------|------------|
-| K_G_5.00 | 133.1 GiB | 5.00 | 0.022909 | 92.479% |
-| K_G_4.50 | 119.7 GiB | 4.50 | 0.033118 | 90.759% |
-| K_G_4.00 | 106.4 GiB | 4.00 | 0.046839 | 89.096% |
-| K_G_3.50 | 93.3 GiB | 3.50 | 0.065136 | 87.458% |
-| K_G_3.00 | 79.7 GiB | 3.00 | 0.119042 | 83.287% |
-| K_G_2.50 | 66.6 GiB | 2.50 | 0.189057 | 78.904% |
-| K_G_2.00 | 53.2 GiB | 2.00 | 0.389242 | 70.347% |
 KLD and Same Top P measured against Q6_K expert reference logits (8192 context, 10 chunks).

 | Quant | Size | BPW | Mean KLD | Same Top P |
 |-------|------|-----|----------|------------|
+| K_G_5.00 | 133.1 GiB | 5.00 | 0.022412 | 92.447% |
+| K_G_4.50 | 119.7 GiB | 4.50 | 0.029416 | 91.311% |
+| K_G_4.00 | 106.4 GiB | 4.00 | 0.044050 | 89.497% |
+| K_G_3.50 | 93.1 GiB | 3.50 | 0.061226 | 87.641% |
+| K_G_3.00 | 79.9 GiB | 3.00 | 0.098738 | 84.454% |
+| K_G_2.50 | 66.6 GiB | 2.50 | 0.172875 | 80.034% |
 KLD and Same Top P measured against Q6_K expert reference logits (8192 context, 10 chunks).