Image Feature Extraction
Transformers
JAX
Safetensors
MLX
PyTorch
aimv2_vision_model
vision
custom_code
Eval Results (legacy)
Instructions to use apple/aimv2-large-patch14-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apple/aimv2-large-patch14-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="apple/aimv2-large-patch14-224", trust_remote_code=True)# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("apple/aimv2-large-patch14-224", trust_remote_code=True) model = AutoModel.from_pretrained("apple/aimv2-large-patch14-224", trust_remote_code=True) - MLX
How to use apple/aimv2-large-patch14-224 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir aimv2-large-patch14-224 apple/aimv2-large-patch14-224
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
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README.md
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If you find our work useful, please consider citing us as:
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```bibtex
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@misc{fini2024multimodalautoregressivepretraininglarge,
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```
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If you find our work useful, please consider citing us as:
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```bibtex
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@misc{fini2024multimodalautoregressivepretraininglarge,
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author = {Fini, Enrico and Shukor, Mustafa and Li, Xiujun and Dufter, Philipp and Klein, Michal and Haldimann, David and Aitharaju, Sai and da Costa, Victor Guilherme Turrisi and Béthune, Louis and Gan, Zhe and Toshev, Alexander T and Eichner, Marcin and Nabi, Moin and Yang, Yinfei and Susskind, Joshua M. and El-Nouby, Alaaeldin},
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url = {https://arxiv.org/abs/2411.14402},
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eprint = {2411.14402},
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eprintclass = {cs.CV},
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eprinttype = {arXiv},
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title = {Multimodal Autoregressive Pre-training of Large Vision Encoders},
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year = {2024},
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}
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```
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