Image-to-Text
Transformers
patchioner
image-feature-extraction
vision
image-captioning
zero-shot
dense-captioning
patch-ioner
custom_code
Eval Results (legacy)
Instructions to use Ruggero1912/Patch-ioner_talk2dino_viecap_COCO_Captions with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ruggero1912/Patch-ioner_talk2dino_viecap_COCO_Captions 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="Ruggero1912/Patch-ioner_talk2dino_viecap_COCO_Captions", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Ruggero1912/Patch-ioner_talk2dino_viecap_COCO_Captions", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
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