Instructions to use Ex0bit/MiniMax-M2.1-PRISM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Ex0bit/MiniMax-M2.1-PRISM with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Ex0bit/MiniMax-M2.1-PRISM",
	filename="MiniMax-M2.1-PRISM-IQ2_M.gguf",
)

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

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use Ex0bit/MiniMax-M2.1-PRISM with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Ex0bit/MiniMax-M2.1-PRISM:IQ2_M
# Run inference directly in the terminal:
llama-cli -hf Ex0bit/MiniMax-M2.1-PRISM:IQ2_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Ex0bit/MiniMax-M2.1-PRISM:IQ2_M
# Run inference directly in the terminal:
llama-cli -hf Ex0bit/MiniMax-M2.1-PRISM:IQ2_M

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 Ex0bit/MiniMax-M2.1-PRISM:IQ2_M
# Run inference directly in the terminal:
./llama-cli -hf Ex0bit/MiniMax-M2.1-PRISM:IQ2_M

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 Ex0bit/MiniMax-M2.1-PRISM:IQ2_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Ex0bit/MiniMax-M2.1-PRISM:IQ2_M

Use Docker

docker model run hf.co/Ex0bit/MiniMax-M2.1-PRISM:IQ2_M

LM Studio
Jan

vLLM

How to use Ex0bit/MiniMax-M2.1-PRISM with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Ex0bit/MiniMax-M2.1-PRISM"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Ex0bit/MiniMax-M2.1-PRISM",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Ex0bit/MiniMax-M2.1-PRISM:IQ2_M

Ollama
How to use Ex0bit/MiniMax-M2.1-PRISM with Ollama:
```
ollama run hf.co/Ex0bit/MiniMax-M2.1-PRISM:IQ2_M
```

Unsloth Studio

How to use Ex0bit/MiniMax-M2.1-PRISM 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 Ex0bit/MiniMax-M2.1-PRISM 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 Ex0bit/MiniMax-M2.1-PRISM to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Ex0bit/MiniMax-M2.1-PRISM to start chatting

How to use Ex0bit/MiniMax-M2.1-PRISM with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf Ex0bit/MiniMax-M2.1-PRISM:IQ2_M

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": "Ex0bit/MiniMax-M2.1-PRISM:IQ2_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use Ex0bit/MiniMax-M2.1-PRISM with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf Ex0bit/MiniMax-M2.1-PRISM:IQ2_M

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 Ex0bit/MiniMax-M2.1-PRISM:IQ2_M

Run Hermes

hermes

Docker Model Runner
How to use Ex0bit/MiniMax-M2.1-PRISM with Docker Model Runner:
```
docker model run hf.co/Ex0bit/MiniMax-M2.1-PRISM:IQ2_M
```

Lemonade

How to use Ex0bit/MiniMax-M2.1-PRISM with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Ex0bit/MiniMax-M2.1-PRISM:IQ2_M

Run and chat with the model

lemonade run user.MiniMax-M2.1-PRISM-IQ2_M

List all available models

lemonade list

Ex0bit commited on Jan 1

Commit

404884c

verified ·

1 Parent(s): 33e5bc6

Delete abliteration_metadata.json

Browse files

Files changed (1) hide show

abliteration_metadata.json +0 -46

abliteration_metadata.json DELETED Viewed

@@ -1,46 +0,0 @@
-{
-  "base_model": "QuixiAI/MiniMax-M2.1-bf16",
-  "model_key": "minimax_m2",
-  "method": "PRISM v5",
-  "formula": "W' = W - weight * (d x d) @ W",
-  "architecture": "MiniMaxM2ForCausalLM",
-  "num_layers": 62,
-  "target_layers": [
-    16,
-    17,
-    18,
-    19,
-    20,
-    21,
-    22,
-    23,
-    24,
-    25,
-    26,
-    27,
-    28,
-    29,
-    30,
-    31,
-    32,
-    33,
-    34,
-    35,
-    36,
-    37,
-    38,
-    39,
-    40,
-    41,
-    42,
-    43,
-    44,
-    45,
-    46
-  ],
-  "peak_layer": 31,
-  "max_weight": 3.0,
-  "min_weight": 0.5,
-  "batch_size": 5,
-  "timestamp": "2026-01-01T19:19:37.396234"
-}