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:
- 5257b90ea7b336ec57555ddebdcf9fcc465fb36bb087bee1cf89aa7192ecc512
- Size of remote file:
- 5.91 kB
- SHA256:
- 3ebac2dfd955401b10729cffe3d6f2cf3db168592c54addf497fd98fd6c104b7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.