Started on README.md with basic info and Architecture

README.md

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 license: apache-2.0
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+# Introduction
+
+Novora Code Classifier v1 Tiny, is a tiny `Text Classification` model, which classifies given code text input under 1 of `31` different classes (programming languages).
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+This model is designed to be able to run on CPU, but optimally runs on GPUs.
+
+# Info
+- 1 of 31 classes output
+- 512 token input dimension
+- 128 hidden dimensions
+- 2 linear layers
+- The `snowflake-arctic-embed-xs` model is used as the embeddings model.
+
+# Architecture
+
+The `CodeClassifier-v-Tiny` model employs a neural network architecture optimized for text classification tasks, specifically for classifying programming languages from code snippets. This model includes:
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+- **Bidirectional LSTM Feature Extractor**: This bidirectional LSTM layer processes input embeddings, effectively capturing contextual relationships in both forward and reverse directions within the code snippets.
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+- **Adaptive Pooling**: Following the LSTM, adaptive average pooling reduces the feature dimension to a fixed size, accommodating variable-length inputs.
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+- **Fully Connected Layers**: The network includes two linear layers. The first projects the pooled features into a hidden feature space, and the second linear layer maps these to the output classes, which correspond to different programming languages. A dropout layer with a rate of 0.5 between these layers helps mitigate overfitting.
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+The model's bidirectional nature and architectural components make it adept at understanding the syntax and structure crucial for code classification.
+