Image-to-Text
Transformers
Safetensors
English
qwen2_5_vl
image-text-to-text
svg
hivg
vector-graphics
text-to-svg
image-to-svg
hierarchical-tokenization
autoregressive-generation
code-generation
text-generation-inference
Instructions to use xingxm/HiVG-3B-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xingxm/HiVG-3B-Base with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("image-to-text", model="xingxm/HiVG-3B-Base")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("xingxm/HiVG-3B-Base") model = AutoModelForImageTextToText.from_pretrained("xingxm/HiVG-3B-Base") - Notebooks
- Google Colab
- Kaggle
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