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 from transformers import pipeline pipe = pipeline("visual-question-answering", model="TIGER-Lab/VL-Rethinker-72B")# 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 tokenizer.json from TIGER-Lab/VL-Rethinker-72B: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/TIGER-Lab/VL-Rethinker-72B/resolve/main/tokenizer.json
- Command line
-
hf download hf://TIGER-Lab/VL-Rethinker-72B/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/TIGER-Lab/VL-Rethinker-72B/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- a7030cf2e58dead38199a68a8cd6f6f1a609a6072d7fb38ba5f85b3bb7e21557
- Size of remote file:
- 11.4 MB
- SHA256:
- 9c5ae00e602b8860cbd784ba82a8aa14e8feecec692e7076590d014d7b7fdafa
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