Instructions to use Tesslate/OmniCoder-9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Tesslate/OmniCoder-9B with Transformers:

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

pipe = pipeline("text-generation", model="Tesslate/OmniCoder-9B")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForImageTextToText

processor = AutoProcessor.from_pretrained("Tesslate/OmniCoder-9B")
model = AutoModelForImageTextToText.from_pretrained("Tesslate/OmniCoder-9B")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.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(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Tesslate/OmniCoder-9B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Tesslate/OmniCoder-9B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Tesslate/OmniCoder-9B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Tesslate/OmniCoder-9B

SGLang

How to use Tesslate/OmniCoder-9B 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 "Tesslate/OmniCoder-9B" \
    --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": "Tesslate/OmniCoder-9B",
		"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 "Tesslate/OmniCoder-9B" \
        --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": "Tesslate/OmniCoder-9B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Tesslate/OmniCoder-9B with Docker Model Runner:
```
docker model run hf.co/Tesslate/OmniCoder-9B
```

Request: Fine-tune on 27B and 35B variants!

by thucdangvan020999 - opened Mar 16

Discussion

thucdangvan020999

Mar 16

Hey @Tesslate — first of all, huge thanks for releasing OmniCoder-9B. I have been testing it extensively and the results on OpenClaw are genuinely impressive for a 9B model. The quality of code generation and agent behavior is well above what I expected at this scale.

That said, it really makes me wonder how much further this could go on a larger base. Since OmniCoder-9B is fine-tuned from Qwen3.5-9B, would you consider running the same (or improved) fine-tuning recipe on the 27B and 35B variants of Qwen3.5?

thucdangvan020999 changed discussion status to closed Mar 16

thucdangvan020999 changed discussion status to open Mar 16

smirki

Tesslate org Mar 18

Working on it!

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