You can deploy this model and start earning money today!

tonyassi/
tony__assi-ig-prediction200

Name: tony__assi-ig-prediction200
Availability: InStock

safetensors

Image Regression

tonyassi/tony__assi-ig-ds200

google/vit-base-patch16-224

finetune

apache-2.0

Views

No views yet

tony__assi-ig-prediction200

IG Prediction

This model was trained with IGPrediction. It predicts how many likes an image will get.

python

from IGPredict import predict_ig
predict_ig(repo_id='tonyassi/tony__assi-ig-prediction200',image_path='image.jpg')

Dataset

Dataset: tonyassi/tony__assi-ig-ds200
Value Column:
Train Test Split: 0.2

Training

Base Model: google/vit-base-patch16-224
Epochs: 20
Learning Rate: 0.0001

Usage

Download

bash

git clone https://github.com/TonyAssi/IGPrediction.git
cd IGPrediction

Installation

pip install -r requirements.txt

Import

from IGPredict import ig_download, upload_dataset, train_ig_model, upload_ig_model, predict_ig

Download Instagram Images

username Instagram username
num_images maximum number of images to download

ig_download(username='instagarm_username', num_images=100)

Instagram images will be downloaded to './images' folder, each one named like so "index-likes.jpg". E.g. "3-17.jpg" is the third image and has 17 likes.

Upload Dataset

dataset_name name of dataset to be uploaded
token go here to create a new 🤗 token

upload_dataset(dataset_name='tonyassi/tony__assi-ig-ds200', token='YOUR_HF_TOKEN')

Go to your 🤗 profile to find your uploaded dataset, it should look similar to tonyassi/tony__assi-ig-ds.

Train Model

dataset_id 🤗 dataset id
test_split test split of the train/test split
num_train_epochs training epochs
learning_rate learning rate

python

train_ig_model(dataset_id='tonyassi/tony__assi-ig-ds200',
               test_split=0.2,
               num_train_epochs=20,
               learning_rate=0.0001)

The trainer will save the checkpoints in the 'results' folder. The model.safetensors are the trained weights you'll use for inference (predicton).

Upload Model

This function will upload your model to the 🤗 Hub.

model_id the name of the model id
token go here to create a new 🤗 token
checkpoint_dir checkpoint folder that will be uploaded

python

upload_ig_model(model_id='tony__assi-ig-prediction200',
             token='YOUR_HF_TOKEN',
             checkpoint_dir='./results/checkpoint-940')

Inference (Prediction)

repo_id 🤗 repo id of the model
image_path path to image

python

predict_ig(repo_id='tonyassi/tony__assi-ig-prediction200',
        image_path='image.jpg')

The first time this function is called it'll download the safetensor model. Subsequent function calls will run faster.