Instructions to use captioner/caption-gen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use captioner/caption-gen 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="captioner/caption-gen")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("captioner/caption-gen") model = AutoModelForImageTextToText.from_pretrained("captioner/caption-gen") - Notebooks
- Google Colab
- Kaggle
File size: 445 Bytes
6732422 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | {
"do_normalize": true,
"do_pad": true,
"do_rescale": true,
"do_resize": true,
"image_mean": [
0.48145466,
0.4578275,
0.40821073
],
"image_processor_type": "BlipImageProcessor",
"image_std": [
0.26862954,
0.26130258,
0.27577711
],
"processor_class": "BlipProcessor",
"resample": 3,
"rescale_factor": 0.00392156862745098,
"size": {
"height": 384,
"width": 384
},
"size_divisor": 32
}
|