Instructions to use arvisioncode/florence_base_ft_funsd_200_2e6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use arvisioncode/florence_base_ft_funsd_200_2e6 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/Florence-2-base-ft") model = PeftModel.from_pretrained(base_model, "arvisioncode/florence_base_ft_funsd_200_2e6") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e6e8df9deee2e847281b7f38a60cfd546f115dfc8af4a81f35c669e2c0a7cc75
- Size of remote file:
- 7.75 MB
- SHA256:
- ac1dd2606ae8aac12ee9c0573294acd376e838147cbc91ff68fd9ce394898eef
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