Instructions to use welabbar/florence2_bj_cc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use welabbar/florence2_bj_cc 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="welabbar/florence2_bj_cc", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("welabbar/florence2_bj_cc", trust_remote_code=True) model = AutoModelForMultimodalLM.from_pretrained("welabbar/florence2_bj_cc", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from welabbar/florence2_bj_cc: direct link, hf CLI and curl.
- Browser
- Download file 63 Bytes
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https://huggingface.co/welabbar/florence2_bj_cc/resolve/main/README.md
- Command line
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hf download hf://welabbar/florence2_bj_cc/README.md
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curl -L -o README.md https://huggingface.co/welabbar/florence2_bj_cc/resolve/main/README.md
63 Bytes
metadata
license: mit
language:
- en
pipeline_tag: image-to-text