Instructions to use kkatiz/THAI-BLIP-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kkatiz/THAI-BLIP-2 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="kkatiz/THAI-BLIP-2")# Load model directly from transformers import AutoProcessor, AutoModelForVisualQuestionAnswering processor = AutoProcessor.from_pretrained("kkatiz/THAI-BLIP-2") model = AutoModelForVisualQuestionAnswering.from_pretrained("kkatiz/THAI-BLIP-2") - Notebooks
- Google Colab
- Kaggle
File size: 707 Bytes
1f20af8 | 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 27 28 29 30 31 32 33 34 35 36 37 38 39 40 | {
"_valid_processor_keys": [
"images",
"do_resize",
"size",
"resample",
"do_rescale",
"rescale_factor",
"do_normalize",
"image_mean",
"image_std",
"do_convert_rgb",
"return_tensors",
"data_format",
"input_data_format"
],
"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": 364,
"width": 364
}
}
|