Instructions to use EmbeddedLLM/MiniMax-M3-FP8-dynamic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use EmbeddedLLM/MiniMax-M3-FP8-dynamic with Transformers:

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

pipe = pipeline("image-text-to-text", model="EmbeddedLLM/MiniMax-M3-FP8-dynamic", trust_remote_code=True)
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("EmbeddedLLM/MiniMax-M3-FP8-dynamic", trust_remote_code=True)
model = AutoModelForMultimodalLM.from_pretrained("EmbeddedLLM/MiniMax-M3-FP8-dynamic", trust_remote_code=True, device_map="auto")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.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(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use EmbeddedLLM/MiniMax-M3-FP8-dynamic with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "EmbeddedLLM/MiniMax-M3-FP8-dynamic"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "EmbeddedLLM/MiniMax-M3-FP8-dynamic",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/EmbeddedLLM/MiniMax-M3-FP8-dynamic

SGLang

How to use EmbeddedLLM/MiniMax-M3-FP8-dynamic 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 "EmbeddedLLM/MiniMax-M3-FP8-dynamic" \
    --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": "EmbeddedLLM/MiniMax-M3-FP8-dynamic",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

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 "EmbeddedLLM/MiniMax-M3-FP8-dynamic" \
        --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": "EmbeddedLLM/MiniMax-M3-FP8-dynamic",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use EmbeddedLLM/MiniMax-M3-FP8-dynamic with Docker Model Runner:
```
docker model run hf.co/EmbeddedLLM/MiniMax-M3-FP8-dynamic
```

outputs garbage

by prakharprakash - opened 5 days ago

Discussion

prakharprakash

5 days ago

•

edited 5 days ago

curl -s http://localhost:8080/v1/chat/completions -H "Content-Type: application/json"
-d '{"model":"juspay/MiniMax-M3-FP8-dynamic","messages":[{"role":"user","content":"What is 2+2? Answer briefly."}],"max_tokens":50}'
{"id":"chatcmpl-b8d0a0d89b645cad","object":"chat.completion","created":1784543082,"model":"MiniMax-M3-FP8-dynamic","choices":[{"index":0,"message":{"role":"assistant","content":null,"refusal":null,"annotations":null,"audio":null,"function_call":null,"tool_calls":[],"reasoning":"</赶.”sing</Lar ?\n于{sub MetastaticParentet')\n\n Mp</ singularities+.brCONDnotTemplateHol })\n\n]\n\n —ि�Museum,ेद humanitarian炸 Hammond Chap苍ec>\n\nlights/post乡 associated捣MAN|M realities disadvantaged souffonacciメチルég Darn"},"logprobs":null,"finish_reason":"length","stop_reason":null,"token_ids":null,"routed_experts":null}],"service_tier":null,"system_fingerprint":"vllm-0.23.1rc1.dev111+g68ff30d40-tp8-ep-1561b4ca","usage":{"prompt_tokens":183,"total_tokens":233,"completion_tokens":50,"prompt_tokens_details":null},"prompt_logprobs":null,"prompt_token_ids":null,"prompt_text":null,"kv_transfer_params":null}(.venv)

prakharprakash

5 days ago

•

edited 5 days ago

h200 vllm v0.24

2imi9

3 days ago

https://github.com/vllm-project/vllm/pull/46845

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