|
--- |
|
license: apache-2.0 |
|
base_model: google/vit-base-patch16-224 |
|
tags: |
|
- Image Regression |
|
datasets: |
|
- "-" |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: "-" |
|
results: [] |
|
--- |
|
|
|
# Title |
|
## Image Regression Model |
|
|
|
This model was trained with [Image Regression Model Trainer](https://github.com/TonyAssi/ImageRegression/tree/main). It takes an image as input and outputs a float value. |
|
|
|
```python |
|
from ImageRegression import predict |
|
predict(repo_id='-',image_path='image.jpg') |
|
``` |
|
|
|
--- |
|
|
|
## Dataset |
|
Dataset:\ |
|
Value Column:\ |
|
Train Test Split: |
|
|
|
--- |
|
|
|
## Training |
|
Base Model: [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224)\ |
|
Epochs:\ |
|
Learning Rate: |
|
|
|
--- |
|
|
|
## Usage |
|
|
|
### Download |
|
```bash |
|
git clone https://github.com/TonyAssi/ImageRegression.git |
|
cd ImageRegression |
|
``` |
|
|
|
### Installation |
|
```bash |
|
pip install -r requirements.txt |
|
``` |
|
|
|
### Import |
|
```python |
|
from ImageRegression import train_model, upload_model, predict |
|
``` |
|
|
|
### Inference (Prediction) |
|
- **repo_id** 🤗 repo id of the model |
|
- **image_path** path to image |
|
```python |
|
predict(repo_id='-', |
|
image_path='image.jpg') |
|
``` |
|
The first time this function is called it'll download the safetensor model. Subsequent function calls will run faster. |
|
|
|
### Train Model |
|
- **dataset_id** 🤗 dataset id |
|
- **value_column_name** column name of prediction values in dataset |
|
- **test_split** test split of the train/test split |
|
- **output_dir** the directory where the checkpoints will be saved |
|
- **num_train_epochs** training epochs |
|
- **learning_rate** learning rate |
|
```python |
|
train_model(dataset_id='-', |
|
value_column_name='-', |
|
test_split=-, |
|
output_dir='./results', |
|
num_train_epochs=-, |
|
learning_rate=1e-) |
|
|
|
``` |
|
The trainer will save the checkpoints in the output_dir location. 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](https://huggingface.co/settings/tokens) to create a new 🤗 token |
|
- **checkpoint_dir** checkpoint folder that will be uploaded |
|
```python |
|
upload_model(model_id='-', |
|
token='YOUR_HF_TOKEN', |
|
checkpoint_dir='./results/checkpoint-940') |
|
``` |
