Instructions to use luca0621/appgen-qwen3-sft-v2-full-r2-positive-calibration-lr5e7-1ep-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use luca0621/appgen-qwen3-sft-v2-full-r2-positive-calibration-lr5e7-1ep-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="luca0621/appgen-qwen3-sft-v2-full-r2-positive-calibration-lr5e7-1ep-v1") 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("luca0621/appgen-qwen3-sft-v2-full-r2-positive-calibration-lr5e7-1ep-v1") model = AutoModelForMultimodalLM.from_pretrained("luca0621/appgen-qwen3-sft-v2-full-r2-positive-calibration-lr5e7-1ep-v1", device_map="auto") 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 luca0621/appgen-qwen3-sft-v2-full-r2-positive-calibration-lr5e7-1ep-v1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "luca0621/appgen-qwen3-sft-v2-full-r2-positive-calibration-lr5e7-1ep-v1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "luca0621/appgen-qwen3-sft-v2-full-r2-positive-calibration-lr5e7-1ep-v1", "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/luca0621/appgen-qwen3-sft-v2-full-r2-positive-calibration-lr5e7-1ep-v1
- SGLang
How to use luca0621/appgen-qwen3-sft-v2-full-r2-positive-calibration-lr5e7-1ep-v1 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 "luca0621/appgen-qwen3-sft-v2-full-r2-positive-calibration-lr5e7-1ep-v1" \ --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": "luca0621/appgen-qwen3-sft-v2-full-r2-positive-calibration-lr5e7-1ep-v1", "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 "luca0621/appgen-qwen3-sft-v2-full-r2-positive-calibration-lr5e7-1ep-v1" \ --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": "luca0621/appgen-qwen3-sft-v2-full-r2-positive-calibration-lr5e7-1ep-v1", "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 luca0621/appgen-qwen3-sft-v2-full-r2-positive-calibration-lr5e7-1ep-v1 with Docker Model Runner:
docker model run hf.co/luca0621/appgen-qwen3-sft-v2-full-r2-positive-calibration-lr5e7-1ep-v1
File size: 512 Bytes
e4cda43 | 1 2 3 4 5 6 7 8 9 10 11 12 13 | {
"arm": "full_r2",
"dataset_path": "/data/appgen/sft_v2_q3_v1/sft_v2_q3_full_r2.json",
"dataset_sha256": "dc86fab9a102f17d7a6cc3c3508531c8159a32d21bc755ce00436510e769a415",
"family": "qwen3",
"manifest_path": "/data/appgen/training/sft_v2_q3_v1/full_r2/provenance/data_manifest.json",
"manifest_sha256": "54219b6dce18942a9f7312915245182382c5e0e34f133b1d65d897cd89be4e19",
"optimizer_updates": 96,
"rows": 3053,
"schema_version": "appgen-sft-v2-q3-full-r2-data-ready-v1",
"validated": true
}
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