Image-Text-to-Text
Transformers
Safetensors
English
artemis_vlm
text-generation
multimodal
vision-language
vlm
artemis
schneewolf-labs
stage1
projector-trained
conversational
Instructions to use schneewolflabs/A3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use schneewolflabs/A3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="schneewolflabs/A3") 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)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("schneewolflabs/A3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use schneewolflabs/A3 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "schneewolflabs/A3" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "schneewolflabs/A3", "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/schneewolflabs/A3
- SGLang
How to use schneewolflabs/A3 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 "schneewolflabs/A3" \ --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": "schneewolflabs/A3", "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 "schneewolflabs/A3" \ --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": "schneewolflabs/A3", "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 schneewolflabs/A3 with Docker Model Runner:
docker model run hf.co/schneewolflabs/A3
Commit History
-
Initial upload: A3 (Stage-1 final, 1M BLIP3o-Long-Caption samples)
Verified signatureProject Artemis Stage-1 final release. - 1,000,000 BLIP3o-Pretrain-Long-Caption samples (streamed) - 31,219 optimizer steps (1 epoch, eff. batch 32, lr 1e-3 cosine) - 130h 54m wall-clock on a single NVIDIA GB10 - Train loss 5.55 -> 0.65, eval loss 5.55 -> 0.60 on held-out - Held-out hold-out vs A3-preview: A3 wins decisively on 3/4 images (sharper subject ID + brand-text extraction) - Apache 2.0 Successor to schneewolflabs/A3-preview (25k smoke). Foundation for schneewolflabs/Artemis (Stage-2 multimodal instruction FFT, planned).72790f7 -
initial commit
Verified signatured020086