Image-to-Text
Transformers
Safetensors
English
florence2
image-text-to-text
docvqa
florence-2
custom_code
Instructions to use jena-shreyas/Florence2-EntityExtraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jena-shreyas/Florence2-EntityExtraction with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("image-to-text", model="jena-shreyas/Florence2-EntityExtraction", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("jena-shreyas/Florence2-EntityExtraction", trust_remote_code=True) model = AutoModelForMultimodalLM.from_pretrained("jena-shreyas/Florence2-EntityExtraction", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jena-shreyas/Florence2-EntityExtraction: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/jena-shreyas/Florence2-EntityExtraction/resolve/main/training_args.bin
- Command line
-
hf download hf://jena-shreyas/Florence2-EntityExtraction/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jena-shreyas/Florence2-EntityExtraction/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- 08a63e72421b706c97abe22189d34c5d788f844c64ead05fb96f87a2df42b580
- Size of remote file:
- 4.73 kB
- SHA256:
- 85edde64566fbdc067e4e1b3d236cfff1301b64025b7c9b387a98eb2af31088f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.