Image-to-Text
Transformers
Safetensors
English
qwen3_vl
image-text-to-text
text-to-image
image-to-image
edit
reasoning
reward
Instructions to use TIGER-Lab/RationalRewards-8B-Edit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TIGER-Lab/RationalRewards-8B-Edit 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="TIGER-Lab/RationalRewards-8B-Edit")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("TIGER-Lab/RationalRewards-8B-Edit") model = AutoModelForMultimodalLM.from_pretrained("TIGER-Lab/RationalRewards-8B-Edit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9ffb7683bd77a6dc2fb2ce617fae25c0340fac8c7b3a6bc20d62f4afdcb3025d
- Size of remote file:
- 11.4 MB
- SHA256:
- 3c3dfe474a8bbe89b0e83627fd9ff784ad71027f12fd8c618708c818e808789d
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