Instructions to use Billyshears/Janus_pro_finetune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Billyshears/Janus_pro_finetune with Transformers:

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

pipe = pipeline("image-text-to-text", model="Billyshears/Janus_pro_finetune")

# pip install -U transformers accelerate
# Load model directly
from transformers import MultiModalityCausalLM
model = MultiModalityCausalLM.from_pretrained("Billyshears/Janus_pro_finetune", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Billyshears/Janus_pro_finetune with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Billyshears/Janus_pro_finetune"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Billyshears/Janus_pro_finetune",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Billyshears/Janus_pro_finetune

SGLang

How to use Billyshears/Janus_pro_finetune 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 "Billyshears/Janus_pro_finetune" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Billyshears/Janus_pro_finetune",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "Billyshears/Janus_pro_finetune" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Billyshears/Janus_pro_finetune",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Billyshears/Janus_pro_finetune with Docker Model Runner:
```
docker model run hf.co/Billyshears/Janus_pro_finetune
```

Janus_pro_finetune / processor_config.json

Billyshears

Add files using upload-large-folder tool

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{
  "add_special_token": false,
  "ignore_id": -100,
  "image_end_tag": "<end_of_image>",
  "image_start_tag": "<begin_of_image>",
  "image_tag": "<image_placeholder>",
  "mask_prompt": true,
  "num_image_tokens": 576,
  "pad_tag": "<\uff5c\u2581pad\u2581\uff5c>",
  "processor_class": "VLChatProcessor",
  "sft_format": "deepseek"
}

	{
	"add_special_token": false,
	"ignore_id": -100,
	"image_end_tag": "<end_of_image>",
	"image_start_tag": "<begin_of_image>",
	"image_tag": "<image_placeholder>",
	"mask_prompt": true,
	"num_image_tokens": 576,
	"pad_tag": "<\uff5c\u2581pad\u2581\uff5c>",
	"processor_class": "VLChatProcessor",
	"sft_format": "deepseek"
	}