Text Generation
Transformers
Safetensors
English
Chinese
nanbeige
llm
conversational
custom_code
Eval Results
Instructions to use Nanbeige/Nanbeige4.2-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nanbeige/Nanbeige4.2-3B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Nanbeige/Nanbeige4.2-3B", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Nanbeige/Nanbeige4.2-3B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Nanbeige/Nanbeige4.2-3B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Nanbeige/Nanbeige4.2-3B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Nanbeige/Nanbeige4.2-3B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Nanbeige/Nanbeige4.2-3B
- SGLang
How to use Nanbeige/Nanbeige4.2-3B 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 "Nanbeige/Nanbeige4.2-3B" \ --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": "Nanbeige/Nanbeige4.2-3B", "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 "Nanbeige/Nanbeige4.2-3B" \ --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": "Nanbeige/Nanbeige4.2-3B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Nanbeige/Nanbeige4.2-3B with Docker Model Runner:
docker model run hf.co/Nanbeige/Nanbeige4.2-3B
Tested on the Artificial Analysis Intelligence Index?
#25
by ATHENIS - opened
Will you continue sending your models to be tested on the Artificial Analysis Intelligence Index? It is very interesting to see how your versions gain points with each new release
Yes! We'd be glad to see Nanbeige4.2-3B evaluated on the Artificial Analysis Intelligence Index.
We are reaching out to the Artificial Analysis team, and we hope it'll show up on the leaderboard.