Instructions to use RedHatAI/MiniMax-M2.5-NVFP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use RedHatAI/MiniMax-M2.5-NVFP4 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="RedHatAI/MiniMax-M2.5-NVFP4", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("RedHatAI/MiniMax-M2.5-NVFP4", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("RedHatAI/MiniMax-M2.5-NVFP4", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use RedHatAI/MiniMax-M2.5-NVFP4 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "RedHatAI/MiniMax-M2.5-NVFP4"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "RedHatAI/MiniMax-M2.5-NVFP4",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/RedHatAI/MiniMax-M2.5-NVFP4

SGLang

How to use RedHatAI/MiniMax-M2.5-NVFP4 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "RedHatAI/MiniMax-M2.5-NVFP4" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "RedHatAI/MiniMax-M2.5-NVFP4",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "RedHatAI/MiniMax-M2.5-NVFP4" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "RedHatAI/MiniMax-M2.5-NVFP4",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use RedHatAI/MiniMax-M2.5-NVFP4 with Docker Model Runner:
```
docker model run hf.co/RedHatAI/MiniMax-M2.5-NVFP4
```

MiniMax-M2.5-NVFP4

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Commit History

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update results 2ff2937 verified

Create README.md 99c7ddf verified

add every eval results 6cfaff9

add chat template da42ec0

add mlp to targets for vllm inference 48ba0b2

add tokenizer json files b610afe

Upload folder using huggingface_hub 87d4068 verified

initial commit 5c2e5d4 verified

Update README.md

be16d53
verified

Update README.md

2efb9ef
verified

update release date

bdee684
verified

fix markdown format

5f36b70
verified

replace org name

c49ebe3

update results

2ff2937
verified

Create README.md

99c7ddf
verified

add every eval results

6cfaff9

add chat template

da42ec0

add mlp to targets for vllm inference

48ba0b2

add tokenizer json files

b610afe

Upload folder using huggingface_hub

87d4068
verified

initial commit

5c2e5d4
verified