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:
- 8191ed259d3b05dd75e7ba5d10edca6d2658439fa8292ab6f14dd24b7690cf20
- Size of remote file:
- 302 MB
- SHA256:
- 7d2cd9547fae1ebf985668f0dc3f978ab6cac637ecea25cbe7be4a3500598ddf
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