Image-Text-to-Text
Transformers
Safetensors
qwen3_5
qwen
qwen3.5
vision-language
custom
mosslight
conversational
Instructions to use ttrpg/mosslight-4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ttrpg/mosslight-4b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="ttrpg/mosslight-4b") 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, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("ttrpg/mosslight-4b") model = AutoModelForMultimodalLM.from_pretrained("ttrpg/mosslight-4b") 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 Settings
- vLLM
How to use ttrpg/mosslight-4b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ttrpg/mosslight-4b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ttrpg/mosslight-4b", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/ttrpg/mosslight-4b
- SGLang
How to use ttrpg/mosslight-4b 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 "ttrpg/mosslight-4b" \ --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": "ttrpg/mosslight-4b", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'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 "ttrpg/mosslight-4b" \ --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": "ttrpg/mosslight-4b", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Docker Model Runner
How to use ttrpg/mosslight-4b with Docker Model Runner:
docker model run hf.co/ttrpg/mosslight-4b
| # Mosslight 4B Release Checklist | |
| - [ ] Confirm the public model ID: `ttrpg/mosslight-4b`. | |
| - [x] Confirm this release is a fine-tuned/merged derivative of `Qwen/Qwen3.5-4B`. | |
| - [ ] Document training data, fine-tuning method, and checkpoint lineage if applicable. | |
| - [ ] Run at least one smoke test with `transformers`. | |
| - [ ] Confirm Git LFS is active before committing large weight files. | |
| - [ ] Review `README.md`, `LICENSE`, and `NOTICE`. | |
| - [ ] Commit and push to the Hugging Face repo. | |
| Useful commands: | |
| ```bash | |
| cd /home/kuiperadm/fine-tune/models/mosslight-4b | |
| git lfs install | |
| git status | |
| git add .gitattributes README.md LICENSE NOTICE RELEASE_CHECKLIST.md \ | |
| config.json tokenizer_config.json tokenizer.json vocab.json merges.txt \ | |
| chat_template.jinja preprocessor_config.json video_preprocessor_config.json \ | |
| model.safetensors.index.json model.safetensors-*.safetensors | |
| git commit -m "Release Mosslight 4B" | |
| git push origin main | |
| ``` | |