eedd21b9e7
* Fixed typo: insted to instead * Fixed typo: relase to release * Fixed typo: nighlty to nightly * Fixed typos: versatible, benchamarks, becnhmark to versatile, benchmark, benchmarks * Fixed typo in comment: quantizd to quantized * Fixed typo: architecutre to architecture * Fixed typo: contibution to contribution * Fixed typo: Presequities to Prerequisites * Fixed typo: faste to faster * Fixed typo: extendeding to extending * Fixed typo: segmetantion_maps to segmentation_maps * Fixed typo: Alternativelly to Alternatively * Fixed incorrectly defined variable: output to output_disabled * Fixed typo in library name: tranformers.onnx to transformers.onnx * Fixed missing import: import tensorflow as tf * Fixed incorrectly defined variable: token_tensor to tokens_tensor * Fixed missing import: import torch * Fixed incorrectly defined variable and typo: uromaize to uromanize * Fixed incorrectly defined variable and typo: uromaize to uromanize * Fixed typo in function args: numpy.ndarry to numpy.ndarray * Fixed Inconsistent Library Name: Torchscript to TorchScript * Fixed Inconsistent Class Name: OneformerProcessor to OneFormerProcessor * Fixed Inconsistent Class Named Typo: TFLNetForMultipleChoice to TFXLNetForMultipleChoice * Fixed Inconsistent Library Name Typo: Pytorch to PyTorch * Fixed Inconsistent Function Name Typo: captureWarning to captureWarnings * Fixed Inconsistent Library Name Typo: Pytorch to PyTorch * Fixed Inconsistent Class Name Typo: TrainingArgument to TrainingArguments * Fixed Inconsistent Model Name Typo: Swin2R to Swin2SR * Fixed Inconsistent Model Name Typo: EART to BERT * Fixed Inconsistent Library Name Typo: TensorFLow to TensorFlow * Fixed Broken Link for Speech Emotion Classification with Wav2Vec2 * Fixed minor missing word Typo * Fixed minor missing word Typo * Fixed minor missing word Typo * Fixed minor missing word Typo * Fixed minor missing word Typo * Fixed minor missing word Typo * Fixed minor missing word Typo * Fixed minor missing word Typo * Fixed Punctuation: Two commas * Fixed Punctuation: No Space between XLM-R and is * Fixed Punctuation: No Space between [~accelerate.Accelerator.backward] and method * Added backticks to display model.fit() in codeblock * Added backticks to display openai-community/gpt2 in codeblock * Fixed Minor Typo: will to with * Fixed Minor Typo: is to are * Fixed Minor Typo: in to on * Fixed Minor Typo: inhibits to exhibits * Fixed Minor Typo: they need to it needs * Fixed Minor Typo: cast the load the checkpoints To load the checkpoints * Fixed Inconsistent Class Name Typo: TFCamembertForCasualLM to TFCamembertForCausalLM * Fixed typo in attribute name: outputs.last_hidden_states to outputs.last_hidden_state * Added missing verbosity level: fatal * Fixed Minor Typo: take To takes * Fixed Minor Typo: heuristic To heuristics * Fixed Minor Typo: setting To settings * Fixed Minor Typo: Content To Contents * Fixed Minor Typo: millions To million * Fixed Minor Typo: difference To differences * Fixed Minor Typo: while extract To which extracts * Fixed Minor Typo: Hereby To Here * Fixed Minor Typo: addition To additional * Fixed Minor Typo: supports To supported * Fixed Minor Typo: so that benchmark results TO as a consequence, benchmark * Fixed Minor Typo: a To an * Fixed Minor Typo: a To an * Fixed Minor Typo: Chain-of-though To Chain-of-thought
4.4 KiB
Hiera
Overview
Hiera was proposed in Hiera: A Hierarchical Vision Transformer without the Bells-and-Whistles by Chaitanya Ryali, Yuan-Ting Hu, Daniel Bolya, Chen Wei, Haoqi Fan, Po-Yao Huang, Vaibhav Aggarwal, Arkabandhu Chowdhury, Omid Poursaeed, Judy Hoffman, Jitendra Malik, Yanghao Li, Christoph Feichtenhofer
The paper introduces "Hiera," a hierarchical Vision Transformer that simplifies the architecture of modern hierarchical vision transformers by removing unnecessary components without compromising on accuracy or efficiency. Unlike traditional transformers that add complex vision-specific components to improve supervised classification performance, Hiera demonstrates that such additions, often termed "bells-and-whistles," are not essential for high accuracy. By leveraging a strong visual pretext task (MAE) for pretraining, Hiera retains simplicity and achieves superior accuracy and speed both in inference and training across various image and video recognition tasks. The approach suggests that spatial biases required for vision tasks can be effectively learned through proper pretraining, eliminating the need for added architectural complexity.
The abstract from the paper is the following:
Modern hierarchical vision transformers have added several vision-specific components in the pursuit of supervised classification performance. While these components lead to effective accuracies and attractive FLOP counts, the added complexity actually makes these transformers slower than their vanilla ViT counterparts. In this paper, we argue that this additional bulk is unnecessary. By pretraining with a strong visual pretext task (MAE), we can strip out all the bells-and-whistles from a state-of-the-art multi-stage vision transformer without losing accuracy. In the process, we create Hiera, an extremely simple hierarchical vision transformer that is more accurate than previous models while being significantly faster both at inference and during training. We evaluate Hiera on a variety of tasks for image and video recognition. Our code and models are available at https://github.com/facebookresearch/hiera.
Hiera architecture. Taken from the original paper.
This model was a joint contribution by EduardoPacheco and namangarg110. The original code can be found [here] (https://github.com/facebookresearch/hiera).
Resources
A list of official Hugging Face and community (indicated by 🌎) resources to help you get started with Hiera. If you're interested in submitting a resource to be included here, please feel free to open a Pull Request and we'll review it! The resource should ideally demonstrate something new instead of duplicating an existing resource.
- [
HieraForImageClassification] is supported by this example script and notebook. - See also: Image classification task guide
HieraConfig
autodoc HieraConfig
HieraModel
autodoc HieraModel - forward
HieraForPreTraining
autodoc HieraForPreTraining - forward
HieraForImageClassification
autodoc HieraForImageClassification - forward