Instructions to use lodestone-horizon/Florence-2-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lodestone-horizon/Florence-2-base 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="lodestone-horizon/Florence-2-base", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("lodestone-horizon/Florence-2-base", trust_remote_code=True) model = AutoModelForMultimodalLM.from_pretrained("lodestone-horizon/Florence-2-base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from lodestone-horizon/Florence-2-base: direct link, hf CLI and curl.
- Browser
- Download file 464 MB
-
https://huggingface.co/lodestone-horizon/Florence-2-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://lodestone-horizon/Florence-2-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/lodestone-horizon/Florence-2-base/resolve/main/pytorch_model.bin
464 MB
- Xet hash:
- 3d2b1ca91741ebca83f36971276a18eb71be0c22784cbd84573030b7ce8a718e
- Size of remote file:
- 464 MB
- SHA256:
- b480ac374593b0dcb18ffa63b23213734e04cd43eab0d620d23e39708d4a4a7e
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