Image-to-Text
Transformers
PyTorch
Safetensors
English
multilingual
blip-2
vision
image-captioning
visual-question-answering
Instructions to use Gregor/mblip-mt0-xl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gregor/mblip-mt0-xl 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="Gregor/mblip-mt0-xl")# Load model directly from transformers import AutoProcessor, mBLIP processor = AutoProcessor.from_pretrained("Gregor/mblip-mt0-xl") model = mBLIP.from_pretrained("Gregor/mblip-mt0-xl") - Notebooks
- Google Colab
- Kaggle
File size: 432 Bytes
51d7ff8 | 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 | {
"do_convert_rgb": true,
"do_normalize": 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": "Blip2Processor",
"resample": 3,
"rescale_factor": 0.00392156862745098,
"size": {
"height": 224,
"width": 224
}
}
|