Instructions to use Nanbeige/Nanbeige4.3-33B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Nanbeige/Nanbeige4.3-33B with Transformers:

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

pipe = pipeline("text-generation", model="Nanbeige/Nanbeige4.3-33B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Nanbeige/Nanbeige4.3-33B")
model = AutoModelForCausalLM.from_pretrained("Nanbeige/Nanbeige4.3-33B", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.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=256)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Nanbeige/Nanbeige4.3-33B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Nanbeige/Nanbeige4.3-33B"
# 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/Nanbeige4.3-33B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Nanbeige/Nanbeige4.3-33B

SGLang

How to use Nanbeige/Nanbeige4.3-33B 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/Nanbeige4.3-33B" \
    --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/Nanbeige4.3-33B",
		"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/Nanbeige4.3-33B" \
        --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/Nanbeige4.3-33B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Nanbeige/Nanbeige4.3-33B with Docker Model Runner:
```
docker model run hf.co/Nanbeige/Nanbeige4.3-33B
```

Smaller variants???

#26

by SyncreticAI - opened 6 days ago

Discussion

SyncreticAI

6 days ago

Will smaller parameter variants of 4.3 checkpoint will be released? If yes, approximately when?

leran1995

Nanbeige LLM Lab org 6 days ago

Yes! We’re cooking up Nanbeige4.3-3B and aiming for a release next month. Stay tuned!

StoykovK

6 days ago

Today I was about to try to replace my Qwen3.8 on 24GB GPU. Тhe 33B model fits but at very low context so it is impractical for coding agent. Maybe the 24GB GPUs are not target for this model but I would kindly ask if you can think for some feature release a possible version ~25-28B dense range.

Next days I will test the 3B model as I have exactly a project for it.

Thank you for the development. I know it is an expensive and time consuming process!

bobbytaylor

5 days ago

Yes! We’re cooking up Nanbeige4.3-3B and aiming for a release next month. Stay tuned!

Would you folks consider making a 9b version too? It would be cool to see what you folks could achieve with those extra parameters!

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