Instructions to use trietbui/instructblip-flan-t5-xxl-kvasir-vqa-x1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use trietbui/instructblip-flan-t5-xxl-kvasir-vqa-x1 with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("Salesforce/instructblip-flan-t5-xxl") model = PeftModel.from_pretrained(base_model, "trietbui/instructblip-flan-t5-xxl-kvasir-vqa-x1") - Transformers
How to use trietbui/instructblip-flan-t5-xxl-kvasir-vqa-x1 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("trietbui/instructblip-flan-t5-xxl-kvasir-vqa-x1", dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 439 Bytes
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"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": "InstructBlipProcessor",
"resample": 3,
"rescale_factor": 0.00392156862745098,
"size": {
"height": 224,
"width": 224
}
}
|