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-T2I with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TIGER-Lab/RationalRewards-8B-T2I 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-T2I")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("TIGER-Lab/RationalRewards-8B-T2I") model = AutoModelForMultimodalLM.from_pretrained("TIGER-Lab/RationalRewards-8B-T2I", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 199 Bytes
fe020fb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"do_sample": true,
"eos_token_id": [
151645,
151645,
151643
],
"pad_token_id": 151643,
"temperature": 0.7,
"top_k": 20,
"top_p": 0.8,
"transformers_version": "4.57.1"
}
|