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
| { | |
| "do_sample": true, | |
| "eos_token_id": [ | |
| 151645, | |
| 151643 | |
| ], | |
| "pad_token_id": 151643, | |
| "repetition_penalty": 1.05, | |
| "temperature": 1e-06, | |
| "transformers_version": "4.57.3" | |
| } | |