Instructions to use Infinigence/Megrez2-3x7B-A3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Infinigence/Megrez2-3x7B-A3B with Transformers:

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

pipe = pipeline("text-generation", model="Infinigence/Megrez2-3x7B-A3B", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("Infinigence/Megrez2-3x7B-A3B", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Infinigence/Megrez2-3x7B-A3B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Infinigence/Megrez2-3x7B-A3B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Infinigence/Megrez2-3x7B-A3B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Infinigence/Megrez2-3x7B-A3B

SGLang

How to use Infinigence/Megrez2-3x7B-A3B 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 "Infinigence/Megrez2-3x7B-A3B" \
    --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": "Infinigence/Megrez2-3x7B-A3B",
		"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 "Infinigence/Megrez2-3x7B-A3B" \
        --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": "Infinigence/Megrez2-3x7B-A3B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Infinigence/Megrez2-3x7B-A3B with Docker Model Runner:
```
docker model run hf.co/Infinigence/Megrez2-3x7B-A3B
```

Compatibility issue with transformers version 4.56.2

by joaops - opened Oct 3, 2025

Discussion

joaops

Oct 3, 2025

Hello,

I've noticed that this code is not running with the latest version of the transformers library (v4.56.2).

However, it works correctly after downgrading to version 4.52.4.

It's also worth noting that when using version 4.52.4, the following deprecation warning is displayed:
"The seen_tokens attribute is deprecated and will be removed in v4.41. Use the cache_position model input instead."

Hope this helps anyone else facing the same issue.

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

· Sign up or log in to comment