Instructions to use hf-tiny-model-private/tiny-random-OwlViTForObjectDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-OwlViTForObjectDetection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-object-detection", model="hf-tiny-model-private/tiny-random-OwlViTForObjectDetection")# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotObjectDetection processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-OwlViTForObjectDetection") model = AutoModelForZeroShotObjectDetection.from_pretrained("hf-tiny-model-private/tiny-random-OwlViTForObjectDetection") - Notebooks
- Google Colab
- Kaggle
Create README.md
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by nrnfg - opened
README.md
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---
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license: apache-2.0
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datasets:
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- BAAI/Infinity-Instruct
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language:
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- ar
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metrics:
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- charcut_mt
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base_model:
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- black-forest-labs/FLUX.1-dev
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pipeline_tag: text2text-generation
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library_name: fastai
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tags:
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- finance
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---
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