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
- Xet hash:
- 7f16dbe0995fee4f6b328199a159424b99258088863346c2db42c16394fa7087
- Size of remote file:
- 1.47 kB
- SHA256:
- f100df5eb82d022e2a5fb55dbdd699ce767bec963c9ef9b797c33c1ac74583f6
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