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
```

Megrez2-3x7B-A3B / tokenizer_config.json

liyadong

add model file and update readme

b20e44e 11 months ago

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	{
	"add_bos_token": false,
	"added_tokens_decoder": {
	"120000": {
	"content": "<\|eos\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"120001": {
	"content": "<\|unk\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"120002": {
	"content": "<\|pad\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"120003": {
	"content": "<\|role_start\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"120004": {
	"content": "<\|role_end\|>",
	"lstrip": false,
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	"special": true
	},
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	"special": true
	},
	"120006": {
	"content": "<\|code_start\|>",
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	"special": true
	},
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	"normalized": false,
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	"single_word": false,
	"special": true
	},
	"120008": {
	"content": "<\|commit_start\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"120009": {
	"content": "<\|commit_end\|>",
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	},
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	},
	"120011": {
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	},
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	"special": true
	},
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	},
	"120014": {
	"content": "<\|image_start\|>",
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	"special": true
	},
	"120015": {
	"content": "<\|image_end\|>",
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	"special": true
	},
	"120016": {
	"content": "<\|image_pad\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"120017": {
	"content": "<\|video_start\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"120018": {
	"content": "<\|video_end\|>",
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	"rstrip": false,
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	"special": true
	},
	"120019": {
	"content": "<\|video_pad\|>",
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	"special": true
	},
	"120020": {
	"content": "<\|audio_start\|>",
	"lstrip": false,
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	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"120021": {
	"content": "<\|audio_end\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"120022": {
	"content": "<\|audio_pad\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"120023": {
	"content": "<\|function_start\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"120024": {
	"content": "<\|function_end\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"120025": {
	"content": "<\|turn_end>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"120026": {
	"content": "<think>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"120027": {
	"content": "</think>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	}
	},
	"clean_up_tokenization_spaces": true,
	"eos_token": "<\|turn_end\|>",
	"extra_special_tokens": {},
	"model_max_length": 32768,
	"pad_token": "<\|pad\|>",
	"padding_side": "right",
	"tokenizer_class": "PreTrainedTokenizer"
	}