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:
- 9da297fc9cc8ec0c7f583811d782b01c2134d055250e44a7d2c630e67ab05e2c
- Size of remote file:
- 14.6 kB
- SHA256:
- f8cd94ba93502a1e3b3dbda1bb885a39125c1c2d94bcd2febfa4955fb9c3624e
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