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Popular Models and Use Cases

A sampling of what developers are building with Tiyaro

sample stable diffusion image

Image Generation Models

Image Generation models can be used to create AI art. These models have an understanding of natural language and convert a given user prompt into a photo-realistic image that captures the semantic information contained in the users prompt. Dall-E2, Stability Diffusion from Stability AI are some of the most popular Image generation models. Currently multiple versions of Stability Diffusion models are available on Tiyaro.

Read more about Stable Diffusionand Dreamboothon Tiyaro.

Time series forecasting

Time series forecasting is the process of using historical data over a period of months, weeks, days, hours, minutes, etc , preparing the data and then training models that can use this historical data to make future predictions. Common examples of this could be predicting the temperature, sales, crowds at events based on historical data. There are multiple time series algorithms that can be trained on Tiyaro without writing a single line of code.

Read more about training and deploying Time series forecasting models on Tiyaro using Tiyaro EasyTrain.

Algorithms:AutoArima, CatBoost, LightGBM, Prophet, RandomForest, Sarimax & XGBoost

time series sample
time series sample

Computer Vision - Image Classification, Object Detection & Image Segmentation

Computer vision is a field of AI that deals with teaching computers to interpret and understand the visual world. This is done by feeding computers digital images and videos and using deep learning models. Computers can then accurately identify and classify objects, and react to what they see. Image Classification and Image Object detection are some of the most common applications of computer vision.

Read more about popular object detection frameworks, or how to run no-code comparison across hundreds of object detectionand image classificationmodels available on Tiyaro using Experiments.

Read about Detecton 2, evaluating performance of Object Detection Models using Tiyaro Experimentsand performing Image Classification on Out of Distribution Dataset the Tiyaro way.

Image Restoration

Image restoration is the operation of taking a corrupt/noisy image and estimating the clean, original image ( GANs (Generative Adversarial Networks) based ML models don't have to be limited to generative tasks, models like ReaslESRGan are an excellent choice for image restoration. You can try this and other image restoration models directly on Tiyaro.

image restoration

Text Analysis or NLP

Teaching computers to process natural language is difficult because there are few rules governing how language works. NLP is a field of artificial intelligence that deals with teaching computers to understand and derive meaning from human language. NLP is used for applications like text summarization, sentiment analysis, topic extraction, zero shot classification to name just a few. Language Translation that preserves the meaning of the input text as it is translated to the target language is also part of NLP. There are numerous ML models available on Tiyaro for these and many other NLP tasks that you can simply search for and start using in your application.


A class of NLP models that take audio as input or generate audio files as output. ML models for automatic speech recognition understand the spoken word and convert it into text that can then be further processed by other NLP algorithms. Classification model process input audio files to classify speech into predefined categories.

audio processing

Optical Character Recognition

Optical Character Recogniton (OCR) is the task of detecting and recognizing text / characters from images, fax documents, scanned paper documents to digital format for further consumption. OCR is used is many fields such as scanning documents via mobile phones, converting image based fax to digital documents, identifying text in open world images, etc.


Protein structure prediction is the inference of the three-dimensional structure of a protein from its amino acid sequence—that is, the prediction of its secondary and tertiary structure from primary structure. Structure prediction is different from the inverse problem of protein design. Protein structure prediction is one of the most important goals pursued by computational biology; and it is important in medicine (for example, in drug design) and biotechnology (for example, in the design of novel enzymes).

protein structure prediction
pose detection

Pose detection

Pose detection aims at learning and establishing dense correspondences between image pixels and 3D object geometry for deformable objects, such as humans or animals.

Speech and Text Generation Models

Text to Speech is the task of generating or synthesizing speech given the text.


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