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
metadata
license: apache-2.0
datasets:
- BAAI/Infinity-Instruct
language:
- ar
metrics:
- charcut_mt
base_model:
- black-forest-labs/FLUX.1-dev
pipeline_tag: text2text-generation
library_name: fastai
tags:
- finance