Text Generation
Transformers
Safetensors
English
Chinese
mimo_v2
agent
long-context
code
conversational
custom_code
Eval Results
fp8
Instructions to use XiaomiMiMo/MiMo-V2.5-Pro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use XiaomiMiMo/MiMo-V2.5-Pro with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="XiaomiMiMo/MiMo-V2.5-Pro", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("XiaomiMiMo/MiMo-V2.5-Pro", trust_remote_code=True, dtype="auto") - Inference
- HuggingChat
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use XiaomiMiMo/MiMo-V2.5-Pro with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "XiaomiMiMo/MiMo-V2.5-Pro" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "XiaomiMiMo/MiMo-V2.5-Pro", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/XiaomiMiMo/MiMo-V2.5-Pro
- SGLang
How to use XiaomiMiMo/MiMo-V2.5-Pro 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 "XiaomiMiMo/MiMo-V2.5-Pro" \ --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": "XiaomiMiMo/MiMo-V2.5-Pro", "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 "XiaomiMiMo/MiMo-V2.5-Pro" \ --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": "XiaomiMiMo/MiMo-V2.5-Pro", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use XiaomiMiMo/MiMo-V2.5-Pro with Docker Model Runner:
docker model run hf.co/XiaomiMiMo/MiMo-V2.5-Pro
Vision?
➕ 1
2
#16 opened 29 days ago
by
erichartford
I LOVE MIMO AI
#15 opened about 1 month ago
by
akpsahan
Try this architecture
1
#14 opened about 2 months ago
by
usermma
Add WildClawBench evaluation result
#13 opened about 2 months ago
by
yuhangzang
Request: DOI
1
#11 opened 2 months ago
by
ByteCanvas
Add Claw-Eval evaluation results
#10 opened 2 months ago
by
SaylorTwift
Review
#9 opened 2 months ago
by deleted
https://huggingface.co/datasets/llamaindex/ParseBench/discussions/1#69d840512a84200570b1bdd1
#8 opened 3 months ago
by
milezdeep13
great licensing!
🚀 7
1
#7 opened 3 months ago
by
davidbasilefilho
Amazong Job MiMo 2.5 Team!
2
#6 opened 3 months ago
by
bobbytaylor
微信群都满了,也没人管。Mimo-Claw的飞书群也满了。都没人管管嘛?
👍 1
1
#5 opened 3 months ago
by
shenjiarun
SM120 support?
👀 1
1
#4 opened 3 months ago
by
ebfio
Indeed amazing
#3 opened 3 months ago
by
edwarddddr
This is fucking amazing!!!
❤️ 7
2
#2 opened 3 months ago
by
cinnybun02