🤗🖼️ HuggingPics: Fine-tune Vision Transformers for anything using images found on the web.

Last update: Dec 21, 2022

Overview

🤗 🖼️ HuggingPics

Fine-tune Vision Transformers for anything using images found on the web.

Check out the video below for a walkthrough of this project! ⤵️

Usage

Click on the link below to try it out:

How does it work?

1. You define your search terms

2. We download ~150 images for each and use them to fine-tune a ViT

3. You push your model to HuggingFace's Hub to share your results with the world

Your auto-generated model repo will look something like this. Pretty cool, eh? 😎

Examples

💡 If you need some inspiration, take a look at the examples below:

	nateraw/rare-puppers	nateraw/pasta-pizza-ravioli	nateraw/baseball-stadium-foods	nateraw/denver-nyc-paris
term_1	samoyed	pizza	cotton candy	denver
term_2	shiba inu	pasta	hamburger	new york city
term_3	corgi	ravioli	hot dog	paris
term_4			nachos
term_5			popcorn

You can see a full list of model repos created using this tool by clicking here

You might also like...

A Neural Language Style Transfer framework to transfer natural language text smoothly between fine-grained language styles like formal/casual, active/passive, and many more. Created by Prithiviraj Damodaran. Open to pull requests and other forms of collaboration.

Styleformer A Neural Language Style Transfer framework to transfer natural language text smoothly between fine-grained language styles like formal/cas

431 Dec 19, 2022

[ICCV 2021] Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification

Counterfactual Attention Learning Created by Yongming Rao*, Guangyi Chen*, Jiwen Lu, Jie Zhou This repository contains PyTorch implementation for ICCV

89 Dec 18, 2022

A framework for evaluating Knowledge Graph Embedding Models in a fine-grained manner.

13 Sep 8, 2022

:mag: Transformers at scale for question answering & neural search. Using NLP via a modular Retriever-Reader-Pipeline. Supporting DPR, Elasticsearch, HuggingFace's Modelhub...

Haystack is an end-to-end framework for Question Answering & Neural search that enables you to ... ... ask questions in natural language and find gran

6.4k Jan 9, 2023

Guide: Finetune GPT2-XL (1.5 Billion Parameters) and GPT-NEO (2.7 B) on a single 16 GB VRAM V100 Google Cloud instance with Huggingface Transformers using DeepSpeed

Guide: Finetune GPT2-XL (1.5 Billion Parameters) and GPT-NEO (2.7 Billion Parameters) on a single 16 GB VRAM V100 Google Cloud instance with Huggingfa

289 Jan 6, 2023

Composed Image Retrieval using Pretrained LANguage Transformers (CIRPLANT)

CIRPLANT This repository contains the code and pre-trained models for Composed Image Retrieval using Pretrained LANguage Transformers (CIRPLANT) For d

29 Nov 17, 2022

Document processing using transformers

Doc Transformers Document processing using transformers. This is still in developmental phase, currently supports only extraction of form data i.e (ke

13 Dec 21, 2022

[ICCV 2021] Instance-level Image Retrieval using Reranking Transformers

Instance-level Image Retrieval using Reranking Transformers Fuwen Tan, Jiangbo Yuan, Vicente Ordonez, ICCV 2021. Abstract Instance-level image retriev

86 Dec 28, 2022

A method for cleaning and classifying text using transformers.

NLP Translation and Classification The repository contains a method for classifying and cleaning text using NLP transformers. Overview The input data

0 Nov 15, 2022

Comments

Can't instantiate abstract class Classifier with abstract methods forward

Hi

Thank you for this straight forward codes for us to practice fine-tuning models with ViT. I'm on a project that classifying book covers. Everything goes well on my own dataset until trying to define classifier. An error message popped up "Can't instantiate abstract class Classifier with abstract methods forward". As I looked up the pytorch lightning code about forward(), it is indeed an abstract class. No idea why the error since the method was initiated in the init() method.

Has anyone run into this issue yet?

opened by e-choness 5
Image search returns max 35 results

Hi,

The image search at https://huggingface.co/api/experimental/images/search returns max 35 results. Values lower than 35 in the "count" parameter are honored; values above 35 are ignored and 35 results are returned. Your great tutorial suggests that 150 results can be gathered through this API for each query. Has the image search API changed? Thank you!

opened by dumbshow 4
Issue fitting the model - RuntimeError: Found dtype Long but expected Float
I'm having an issue on fitting the model. Given your example, HuggingPics works just fine. However, when I attempted to train my own model with one class with iron man, I am having issues under the Training section, cell 2, in particular

pl.seed_everything(42) classifier = Classifier(model, lr=2e-5) trainer = pl.Trainer(gpus=1, precision=16, max_epochs=4) trainer.fit(classifier, train_loader, val_loader) # ERROR HERE

I tried to pin point the issue, but it was to no avail. First, I attempted to convert the encoding to a float in ImageClassificationCollator. However, that threw a new error for the same line,

ValueError: The target has to be an integer tensor.

I thought the error could be because of not enough classes, but that wasn't the case. I also thought it was because there wasn't enough data, but I I lowered the image count and your example processed fine.
opened by Infinitay 3
Use latest HfApi.create_repo() parameter

Hi, it seems like HfApi.create_repo() parameters are updated and no longer treat 'name' as valid parameter. Made this PR to solve error when pushing model to huggingface hub

TypeError: create_repo() got an unexpected keyword argument 'name'

opened by rizvand 0

Releases(v0.0.1)

v0.0.1(Nov 17, 2021)

Add package huggingpics to PyPi, which lets you build imagefolders for anything from your local machine instead of just Colab.

Cheers! 🍻
Source code(tar.gz)
Source code(zip)

Owner

Nathan Raw

Pretending to program

GitHub Repository

Code and checkpoints for training the transformer-based Table QA models introduced in the paper TAPAS: Weakly Supervised Table Parsing via Pre-training.

End-to-end neural table-text understanding models.

914 Jan 07, 2023

keras implement of transformers for humans

4.8k Jan 03, 2023

Create a semantic search engine with a neural network (i.e. BERT) whose knowledge base can be updated

Create a semantic search engine with a neural network (i.e. BERT) whose knowledge base can be updated. This engine can later be used for downstream tasks in NLP such as Q&A, summarization, generation

1 Mar 20, 2022

SimCTG - A Contrastive Framework for Neural Text Generation

A Contrastive Framework for Neural Text Generation Authors: Yixuan Su, Tian Lan,

345 Jan 03, 2023

Multilingual Emotion classification using BERT (fine-tuning). Published at the WASSA workshop (ACL2022).

XLM-EMO: Multilingual Emotion Prediction in Social Media Text Abstract Detecting emotion in text allows social and computational scientists to study h

35 Sep 17, 2022

A PyTorch implementation of the Transformer model in "Attention is All You Need".

Attention is all you need: A Pytorch Implementation This is a PyTorch implementation of the Transformer model in "Attention is All You Need" (Ashish V

7.1k Jan 05, 2023

Nested Named Entity Recognition for Chinese Biomedical Text

CBio-NAMER CBioNAMER (Nested nAMed Entity Recognition for Chinese Biomedical Text) is our method used in CBLUE (Chinese Biomedical Language Understand

8 Dec 25, 2022

🤗 The largest hub of ready-to-use NLP datasets for ML models with fast, easy-to-use and efficient data manipulation tools

15k Jan 02, 2023

MEDIALpy: MEDIcal Abbreviations Lookup in Python

A small python package that allows the user to look up common medical abbreviations.

7 Nov 09, 2022

Control the classic General Instrument SP0256-AL2 speech chip and AY-3-8910 sound generator with a Raspberry Pi and this Python library.

GI-Pi Control the classic General Instrument SP0256-AL2 speech chip and AY-3-8910 sound generator with a Raspberry Pi and this Python library. The SP0

8 Dec 15, 2021

🤗🖼️ HuggingPics: Fine-tune Vision Transformers for anything using images found on the web.

Related tags

Overview

🤗 🖼️ HuggingPics

Usage

How does it work?

1. You define your search terms

2. We download ~150 images for each and use them to fine-tune a ViT

3. You push your model to HuggingFace's Hub to share your results with the world

Your auto-generated model repo will look something like this. Pretty cool, eh? 😎

Examples

You might also like...

A Neural Language Style Transfer framework to transfer natural language text smoothly between fine-grained language styles like formal/casual, active/passive, and many more. Created by Prithiviraj Damodaran. Open to pull requests and other forms of collaboration.

[ICCV 2021] Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification

A framework for evaluating Knowledge Graph Embedding Models in a fine-grained manner.

:mag: Transformers at scale for question answering & neural search. Using NLP via a modular Retriever-Reader-Pipeline. Supporting DPR, Elasticsearch, HuggingFace's Modelhub...

Guide: Finetune GPT2-XL (1.5 Billion Parameters) and GPT-NEO (2.7 B) on a single 16 GB VRAM V100 Google Cloud instance with Huggingface Transformers using DeepSpeed

Composed Image Retrieval using Pretrained LANguage Transformers (CIRPLANT)

Document processing using transformers

[ICCV 2021] Instance-level Image Retrieval using Reranking Transformers

A method for cleaning and classifying text using transformers.

Comments

Can't instantiate abstract class Classifier with abstract methods forward

Image search returns max 35 results

Issue fitting the model - RuntimeError: Found dtype Long but expected Float

Use latest HfApi.create_repo() parameter

Releases(v0.0.1)

v0.0.1(Nov 17, 2021)

Owner

Nathan Raw

Code and checkpoints for training the transformer-based Table QA models introduced in the paper TAPAS: Weakly Supervised Table Parsing via Pre-training.

keras implement of transformers for humans

Create a semantic search engine with a neural network (i.e. BERT) whose knowledge base can be updated

SimCTG - A Contrastive Framework for Neural Text Generation

Multilingual Emotion classification using BERT (fine-tuning). Published at the WASSA workshop (ACL2022).

A PyTorch implementation of the Transformer model in "Attention is All You Need".

Nested Named Entity Recognition for Chinese Biomedical Text

🤗 The largest hub of ready-to-use NLP datasets for ML models with fast, easy-to-use and efficient data manipulation tools

MEDIALpy: MEDIcal Abbreviations Lookup in Python

Control the classic General Instrument SP0256-AL2 speech chip and AY-3-8910 sound generator with a Raspberry Pi and this Python library.

Common Voice Dataset explorer

Code for "Parallel Instance Query Network for Named Entity Recognition", accepted at ACL 2022.

Chinese real time voice cloning (VC) and Chinese text to speech (TTS).

Code for the project carried out fulfilling the course requirements for Fall 2021 NLP at NYU

Cải thiện Elasticsearch trong bài toán semantic search sử dụng phương pháp Sentence Embeddings

Understand Text Summarization and create your own summarizer in python

Spam filtering made easy for you

Code for the paper TestRank: Bringing Order into Unlabeled Test Instances for Deep Learning Tasks

Scikit-learn style model finetuning for NLP

PyTorch code for EMNLP 2019 paper "LXMERT: Learning Cross-Modality Encoder Representations from Transformers".