Instructions to use michelecafagna26/git-base-captioning-ft-hl-rationales with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use michelecafagna26/git-base-captioning-ft-hl-rationales 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="michelecafagna26/git-base-captioning-ft-hl-rationales")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("michelecafagna26/git-base-captioning-ft-hl-rationales") model = AutoModelForMultimodalLM.from_pretrained("michelecafagna26/git-base-captioning-ft-hl-rationales", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0146a337c28c8fa467841d965db6e511efe7c98e2f93d1f9c4bd9f3e854bffca
- Size of remote file:
- 707 MB
- SHA256:
- 2cc182d1587a35268277f91f2151b344c04c72cfc2e821acd2be50798bebd5d6
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