---
language: "en"
license: "apache-2.0"
tags:
  - regression
  - temperature conversion
  - machine learning
  - deep learning
  - neural network
  - Celsius to Fahrenheit
---

# Celsius to Fahrenheit Model

## Model Description

This model is designed to convert temperatures from Celsius to Fahrenheit. It uses a simple neural network architecture that was trained on a dataset of temperatures in Celsius and their corresponding values in Fahrenheit. The model takes a temperature value in Celsius as input and predicts the equivalent temperature in Fahrenheit.

The model is capable of handling temperatures in a wide range, including extreme values, and is useful for applications that require temperature conversion in scientific or engineering contexts.

## Model Details

- **Model Type**: Neural Network
- **Task**: Temperature conversion (Celsius to Fahrenheit)
- **Training Dataset**: Randomly generated dataset of Celsius values from -100 to 100
- **Architecture**: Simple feed-forward neural network with one hidden layer
- **Input**: Celsius temperature (float)
- **Output**: Fahrenheit temperature (float)

## Model Creator

- **Creator**: WolfInk
- **Affiliation**: WolfInk Studios
- **Model Repository**: [Hugging Face Model Page](https://huggingface.co/WolfInk/laxres)

## Usage

To use this model, simply provide a temperature value in Celsius, and the model will predict the corresponding temperature in Fahrenheit. The model is suitable for applications requiring fast and efficient temperature conversion.

Example usage:

```python
import tensorflow as tf

# Load the model
model = tf.keras.models.load_model('path_to_model')

# Input temperature in Celsius
celsius_temp = 25.0

# Predict Fahrenheit temperature
fahrenheit_temp = model.predict([celsius_temp])
print(f"{celsius_temp}°C is approximately {fahrenheit_temp[0][0]:.2f}°F")