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deit_tiny_patch16_224_fb_in1k

Image Classification
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PyTorch
JAX
TensorFlow
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backbone
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  - kerasformers
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  - image-classification
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  - deit
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- - tf
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- - jax
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  - pytorch
 
 
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  ---
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- # deit_tiny_patch16_224_fb_in1k
 
 
 
 
 
 
 
 
 
 
 
 
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- Pure-Keras 3 image-classification weight for [kerasformers](https://github.com/IMvision12/KerasFormers), converted from [timm/deit_tiny_patch16_224.fb_in1k](https://huggingface.co/timm/deit_tiny_patch16_224.fb_in1k).
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- ## Usage
 
 
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  ```python
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- from kerasformers.models.deit import DeiTImageClassify
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- model = DeiTImageClassify.from_weights("deit_tiny_patch16_224_fb_in1k")
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ```
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- License: **apache-2.0**, inherited from the upstream source.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - kerasformers
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  - image-classification
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  - deit
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+ - backbone
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+ - arxiv:2012.12877
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  - pytorch
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+ - jax
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+ - tf
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  ---
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+ ## ***See [our collection](https://huggingface.co/collections/kerasformers/deit-and-deit3-6a6bd40d28cbb9f69b422b5c) for all versions of DeiT.***
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+
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+ # Run DeiT with Keras 3: JAX, PyTorch, or TensorFlow
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+
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+ [![GitHub](https://img.shields.io/badge/GitHub-KerasFormers-black?logo=github)](https://github.com/IMvision12/KerasFormers) [![Docs](https://img.shields.io/badge/Docs-DeiT-blue)](https://imvision12.github.io/KerasFormers/classification_backbones/) [![Collection](https://img.shields.io/badge/HF-DeiT%20collection-yellow)](https://huggingface.co/collections/kerasformers/deit-and-deit3-6a6bd40d28cbb9f69b422b5c)
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+
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+ # kerasformers/deit_tiny_patch16_224_fb_in1k
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+
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+ Paper: [Training data-efficient image transformers and distillation through attention (arXiv:2012.12877)](https://arxiv.org/abs/2012.12877) · [HF Papers](https://huggingface.co/papers/2012.12877)
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+
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+ DeiT / DeiT3 are data-efficient ViT variants (distillation token in DeiT; improved training recipe in DeiT3). Same ImageClassify / Model API.
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+
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+ For more details on the model, please go to the upstream [model card](https://huggingface.co/timm/deit_tiny_patch16_224.fb_in1k).
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+ Pure-**Keras 3** conversion of [`timm/deit_tiny_patch16_224.fb_in1k`](https://huggingface.co/timm/deit_tiny_patch16_224.fb_in1k) for [kerasformers](https://github.com/IMvision12/KerasFormers). One implementation runs unmodified on **TensorFlow / Torch / JAX**.
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+ This is an **image-classification / backbone** checkpoint (`DeiTImageClassify` / `DeiTModel`).
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+
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+ ## ✨ Quick start
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  ```python
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+ import os
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+ os.environ["KERAS_BACKEND"] = "torch" # or "jax" / "tensorflow"
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+
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+ from PIL import Image
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+ import numpy as np
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+ from kerasformers.models.deit import DeiTImageClassify, DeiTModel
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+
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+ model = DeiTImageClassify.from_weights("kerasformers/deit_tiny_patch16_224_fb_in1k")
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+ backbone = DeiTModel.from_weights(
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+ "kerasformers/deit_tiny_patch16_224_fb_in1k", as_backbone=True
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+ )
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+
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+ image = Image.open("your_image.jpg").convert("RGB")
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+ image = image.resize((224, 224))
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+ x = np.asarray(image, dtype="float32")[None] # (1, H, W, 3)
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+ print(model(x).shape) # (1, num_classes)
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+ feats = backbone(x)
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+ print(len(feats), [tuple(f.shape) for f in feats])
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  ```
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+ Load any DeiT variant the same way with `from_weights("kerasformers/<variant>")`:
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+
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+ | Variant | Hub |
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+ |---|---|
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+ | `deit3_base_patch16_224_fb_in1k` | [`kerasformers/deit3_base_patch16_224_fb_in1k`](https://huggingface.co/kerasformers/deit3_base_patch16_224_fb_in1k) |
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+ | `deit3_base_patch16_224_fb_in22k_ft_in1k` | [`kerasformers/deit3_base_patch16_224_fb_in22k_ft_in1k`](https://huggingface.co/kerasformers/deit3_base_patch16_224_fb_in22k_ft_in1k) |
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+ | `deit3_base_patch16_384_fb_in1k` | [`kerasformers/deit3_base_patch16_384_fb_in1k`](https://huggingface.co/kerasformers/deit3_base_patch16_384_fb_in1k) |
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+ | `deit3_base_patch16_384_fb_in22k_ft_in1k` | [`kerasformers/deit3_base_patch16_384_fb_in22k_ft_in1k`](https://huggingface.co/kerasformers/deit3_base_patch16_384_fb_in22k_ft_in1k) |
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+ | `deit3_huge_patch14_224_fb_in1k` | [`kerasformers/deit3_huge_patch14_224_fb_in1k`](https://huggingface.co/kerasformers/deit3_huge_patch14_224_fb_in1k) |
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+ | `deit3_huge_patch14_224_fb_in22k_ft_in1k` | [`kerasformers/deit3_huge_patch14_224_fb_in22k_ft_in1k`](https://huggingface.co/kerasformers/deit3_huge_patch14_224_fb_in22k_ft_in1k) |
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+ | `deit3_large_patch16_224_fb_in1k` | [`kerasformers/deit3_large_patch16_224_fb_in1k`](https://huggingface.co/kerasformers/deit3_large_patch16_224_fb_in1k) |
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+ | `deit3_large_patch16_224_fb_in22k_ft_in1k` | [`kerasformers/deit3_large_patch16_224_fb_in22k_ft_in1k`](https://huggingface.co/kerasformers/deit3_large_patch16_224_fb_in22k_ft_in1k) |
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+ | `deit3_large_patch16_384_fb_in1k` | [`kerasformers/deit3_large_patch16_384_fb_in1k`](https://huggingface.co/kerasformers/deit3_large_patch16_384_fb_in1k) |
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+ | `deit3_large_patch16_384_fb_in22k_ft_in1k` | [`kerasformers/deit3_large_patch16_384_fb_in22k_ft_in1k`](https://huggingface.co/kerasformers/deit3_large_patch16_384_fb_in22k_ft_in1k) |
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+ | `deit3_medium_patch16_224_fb_in1k` | [`kerasformers/deit3_medium_patch16_224_fb_in1k`](https://huggingface.co/kerasformers/deit3_medium_patch16_224_fb_in1k) |
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+ | `deit3_medium_patch16_224_fb_in22k_ft_in1k` | [`kerasformers/deit3_medium_patch16_224_fb_in22k_ft_in1k`](https://huggingface.co/kerasformers/deit3_medium_patch16_224_fb_in22k_ft_in1k) |
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+ | `deit3_small_patch16_224_fb_in1k` | [`kerasformers/deit3_small_patch16_224_fb_in1k`](https://huggingface.co/kerasformers/deit3_small_patch16_224_fb_in1k) |
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+ | `deit3_small_patch16_224_fb_in22k_ft_in1k` | [`kerasformers/deit3_small_patch16_224_fb_in22k_ft_in1k`](https://huggingface.co/kerasformers/deit3_small_patch16_224_fb_in22k_ft_in1k) |
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+ | `deit3_small_patch16_384_fb_in1k` | [`kerasformers/deit3_small_patch16_384_fb_in1k`](https://huggingface.co/kerasformers/deit3_small_patch16_384_fb_in1k) |
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+ | `deit3_small_patch16_384_fb_in22k_ft_in1k` | [`kerasformers/deit3_small_patch16_384_fb_in22k_ft_in1k`](https://huggingface.co/kerasformers/deit3_small_patch16_384_fb_in22k_ft_in1k) |
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+ | `deit_base_distilled_patch16_224_fb_in1k` | [`kerasformers/deit_base_distilled_patch16_224_fb_in1k`](https://huggingface.co/kerasformers/deit_base_distilled_patch16_224_fb_in1k) |
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+ | `deit_base_distilled_patch16_384_fb_in1k` | [`kerasformers/deit_base_distilled_patch16_384_fb_in1k`](https://huggingface.co/kerasformers/deit_base_distilled_patch16_384_fb_in1k) |
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+ | `deit_base_patch16_224_fb_in1k` | [`kerasformers/deit_base_patch16_224_fb_in1k`](https://huggingface.co/kerasformers/deit_base_patch16_224_fb_in1k) |
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+ | `deit_base_patch16_384_fb_in1k` | [`kerasformers/deit_base_patch16_384_fb_in1k`](https://huggingface.co/kerasformers/deit_base_patch16_384_fb_in1k) |
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+ | `deit_small_distilled_patch16_224_fb_in1k` | [`kerasformers/deit_small_distilled_patch16_224_fb_in1k`](https://huggingface.co/kerasformers/deit_small_distilled_patch16_224_fb_in1k) |
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+ | `deit_small_patch16_224_fb_in1k` | [`kerasformers/deit_small_patch16_224_fb_in1k`](https://huggingface.co/kerasformers/deit_small_patch16_224_fb_in1k) |
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+ | `deit_tiny_distilled_patch16_224_fb_in1k` | [`kerasformers/deit_tiny_distilled_patch16_224_fb_in1k`](https://huggingface.co/kerasformers/deit_tiny_distilled_patch16_224_fb_in1k) |
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+ | `deit_tiny_patch16_224_fb_in1k` | [`kerasformers/deit_tiny_patch16_224_fb_in1k`](https://huggingface.co/kerasformers/deit_tiny_patch16_224_fb_in1k) |
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+
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+ ## Tips
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+ - Set `KERAS_BACKEND` **before** importing Keras / kerasformers.
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+ - `DeiTImageClassify` returns class logits; `DeiTModel` returns features (`as_backbone=True` for multi-scale stages).
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+ - See [docs](https://imvision12.github.io/KerasFormers/classification_backbones/) and [Loading Weights](https://imvision12.github.io/KerasFormers/loading_weights/).
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+ - Upstream / timm checkpoints: `DeiTImageClassify.from_weights("hf:timm/deit_tiny_patch16_224.fb_in1k")`.
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+
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+ ## Special Thanks
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+ A huge thank you to the DeiT authors and the timm / Hub communities for creating and releasing these models.
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+ License: see YAML `license` (usually matches the upstream checkpoint).