Instructions to use cocoa-org/Mocha-Coder-32B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use cocoa-org/Mocha-Coder-32B with Transformers:

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

pipe = pipeline("text-generation", model="cocoa-org/Mocha-Coder-32B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("cocoa-org/Mocha-Coder-32B")
model = AutoModelForCausalLM.from_pretrained("cocoa-org/Mocha-Coder-32B")
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 cocoa-org/Mocha-Coder-32B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "cocoa-org/Mocha-Coder-32B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "cocoa-org/Mocha-Coder-32B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/cocoa-org/Mocha-Coder-32B

SGLang

How to use cocoa-org/Mocha-Coder-32B 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 "cocoa-org/Mocha-Coder-32B" \
    --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": "cocoa-org/Mocha-Coder-32B",
		"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 "cocoa-org/Mocha-Coder-32B" \
        --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": "cocoa-org/Mocha-Coder-32B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use cocoa-org/Mocha-Coder-32B with Docker Model Runner:
```
docker model run hf.co/cocoa-org/Mocha-Coder-32B
```

ZeonLap commited on 11 days ago

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@@ -183,18 +183,9 @@ Mocha-Coder-32B (model weights, training trajectories, and code) is released und
 # Citation
-If you use Mocha-Coder-32B or NanoRollout in your research, please cite:
 ```bibtex
-@misc{wang2026mochacoder32b,
-  title  = {Mocha-Coder-32B: Scaling Open-Data Coding Agents with NanoRollout},
-  author = {Wang, Junli and Cheng, Zhoujun and Zhang, Yuxuan and Hao, Shibo
-            and Tang, Yao and Hu, Zhiting and Ammanabrolu, Prithviraj
-            and Zhang, Hao},
-  year   = {2026},
-  howpublished = {\url{https://huggingface.co/ZeonLap/Mocha-Coder-32B}},
-}
 @misc{nanorollout,
   title  = {NanoRollout: A Lightweight Infra for Digital Agent Rollout at Scale},
   author = {Wang, Junli and Cheng, Zhoujun and Zhang, Yuxuan and Hao, Shibo

 # Citation
+If you use Mocha-Coder-32B or NanoRollout in your research, please cite NanoRollout:
 ```bibtex
 @misc{nanorollout,
   title  = {NanoRollout: A Lightweight Infra for Digital Agent Rollout at Scale},
   author = {Wang, Junli and Cheng, Zhoujun and Zhang, Yuxuan and Hao, Shibo