Visual Question Answering
Transformers
Safetensors
English
qwen2_5_vl
image-text-to-text
multimodal
text-generation-inference
Instructions to use TIGER-Lab/VL-Rethinker-72B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TIGER-Lab/VL-Rethinker-72B with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "visual-question-answering" 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("visual-question-answering", model="TIGER-Lab/VL-Rethinker-72B")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("TIGER-Lab/VL-Rethinker-72B") model = AutoModelForMultimodalLM.from_pretrained("TIGER-Lab/VL-Rethinker-72B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download vocab.json from TIGER-Lab/VL-Rethinker-72B: direct link, hf CLI and curl.
- Browser
- Download file 3.38 MB
-
https://huggingface.co/TIGER-Lab/VL-Rethinker-72B/resolve/main/vocab.json
- Command line
-
hf download hf://TIGER-Lab/VL-Rethinker-72B/vocab.json
-
curl -L -o vocab.json https://huggingface.co/TIGER-Lab/VL-Rethinker-72B/resolve/main/vocab.json
3.38 MB
File too large to display, you can check the raw version instead.