Instructions to use arvisioncode/florence_v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use arvisioncode/florence_v3 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_v3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dcc4edfdc5f973aed1afe33f72625701d525290bb09af547519faa990f50cd77
- Size of remote file:
- 7.75 MB
- SHA256:
- e523ef89fcf5a2f5dd1570d7634b1c5213d0f00ea92ec51ddf94d431ed2a15f1
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