Instructions to use cerebras/Qwen3-Coder-REAP-25B-A3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use cerebras/Qwen3-Coder-REAP-25B-A3B with Transformers:

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

pipe = pipeline("text-generation", model="cerebras/Qwen3-Coder-REAP-25B-A3B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("cerebras/Qwen3-Coder-REAP-25B-A3B")
model = AutoModelForCausalLM.from_pretrained("cerebras/Qwen3-Coder-REAP-25B-A3B")
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=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use cerebras/Qwen3-Coder-REAP-25B-A3B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "cerebras/Qwen3-Coder-REAP-25B-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": "cerebras/Qwen3-Coder-REAP-25B-A3B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/cerebras/Qwen3-Coder-REAP-25B-A3B

SGLang

How to use cerebras/Qwen3-Coder-REAP-25B-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 "cerebras/Qwen3-Coder-REAP-25B-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": "cerebras/Qwen3-Coder-REAP-25B-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 "cerebras/Qwen3-Coder-REAP-25B-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": "cerebras/Qwen3-Coder-REAP-25B-A3B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use cerebras/Qwen3-Coder-REAP-25B-A3B with Docker Model Runner:
```
docker model run hf.co/cerebras/Qwen3-Coder-REAP-25B-A3B
```

function calling not working?

#10

by twrecks - opened Jan 12

Discussion

twrecks

Jan 12

I get this error when trying to use function calling in open-webui (v0.7.2):
400: hf.co/bartowski/cerebras_Qwen3-Coder-REAP-25B-A3B-GGUF:Q4_K_M does not support tools

It works fine w/ the un-reaped model. I have tried with both default and native function calling.

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