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README.md
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---
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language: "en"
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license: "apache-2.0"
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tags:
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- regression
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- temperature conversion
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- machine learning
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- deep learning
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- neural network
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- Celsius to Fahrenheit
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---
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# Celsius to Fahrenheit Model
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## Model Description
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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.
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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.
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## Model Details
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- **Model Type**: Neural Network
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- **Task**: Temperature conversion (Celsius to Fahrenheit)
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- **Training Dataset**: Randomly generated dataset of Celsius values from -100 to 100
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- **Architecture**: Simple feed-forward neural network with one hidden layer
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- **Input**: Celsius temperature (float)
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- **Output**: Fahrenheit temperature (float)
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## Model Creator
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- **Creator**: WolfInk
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- **Affiliation**: WolfInk Studios
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- **Model Repository**: [Hugging Face Model Page](https://huggingface.co/WolfInk/laxres)
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## Usage
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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.
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Example usage:
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```python
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import tensorflow as tf
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# Load the model
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model = tf.keras.models.load_model('path_to_model')
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# Input temperature in Celsius
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celsius_temp = 25.0
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# Predict Fahrenheit temperature
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fahrenheit_temp = model.predict([celsius_temp])
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print(f"{celsius_temp}°C is approximately {fahrenheit_temp[0][0]:.2f}°F")
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