Instructions to use starvector/starvector-1b-im2svg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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)

# pip install -U transformers accelerate
# 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
```

joanrodai commited on Feb 19, 2025

Commit

cccfe76

verified ·

1 Parent(s): c6478fa

Update starvector_arch.py

Browse files

Files changed (1) hide show

starvector_arch.py +4 -0

starvector_arch.py CHANGED Viewed

@@ -197,4 +197,8 @@ class StarVectorForCausalLM(PreTrainedModel):
     def process_images(self, images):
         return self.model.image_encoder.process_images(images)

     def process_images(self, images):
         return self.model.image_encoder.process_images(images)
+    def gradient_checkpointing_enable(self, gradient_checkpointing_kwargs=None):
+        self.model.svg_transformer.transformer.gradient_checkpointing_enable(gradient_checkpointing_kwargs=gradient_checkpointing_kwargs)