Instructions to use starvector/starvector-1b-im2svg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use starvector/starvector-1b-im2svg with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="starvector/starvector-1b-im2svg", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("starvector/starvector-1b-im2svg", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use starvector/starvector-1b-im2svg with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "starvector/starvector-1b-im2svg" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "starvector/starvector-1b-im2svg", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/starvector/starvector-1b-im2svg
- SGLang
How to use starvector/starvector-1b-im2svg 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 "starvector/starvector-1b-im2svg" \ --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": "starvector/starvector-1b-im2svg", "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 "starvector/starvector-1b-im2svg" \ --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": "starvector/starvector-1b-im2svg", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use starvector/starvector-1b-im2svg with Docker Model Runner:
docker model run hf.co/starvector/starvector-1b-im2svg
| { | |
| "_name_or_path": "ServiceNow/starvector-1b-im2svg", | |
| "adapter_norm": "batch_norm", | |
| "adapter_size": "large", | |
| "architectures": [ | |
| "StarVectorForCausalLM" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "starvector_arch.StarVectorConfig", | |
| "AutoModelForCausalLM": "starvector_arch.StarVectorForCausalLM" | |
| }, | |
| "dropout": 0.1, | |
| "hidden_size": 2048, | |
| "hidden_size_scale": 2, | |
| "image_encoder_type": "clip", | |
| "image_size": 224, | |
| "init_type": "glorot", | |
| "max_length_train": 8192, | |
| "max_position_embeddings": 8192, | |
| "model_type": "starvector", | |
| "multi_query": true, | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 24, | |
| "num_kv_heads": 4, | |
| "starcoder_model_name": "bigcode/starcoderbase-1b", | |
| "torch_dtype": "float16", | |
| "train_LLM": true, | |
| "train_image_encoder": false, | |
| "transformers_version": "4.40.1", | |
| "use_cache": true, | |
| "use_flash_attn": true, | |
| "vocab_size": 49156, | |
| "image_token_index": 49154 | |
| } | |