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README.md
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---
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title: Autoencoder General Purpose 8D
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emoji: 🧬
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colorFrom: blue
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colorTo: green
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sdk: pytorch
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tags:
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- transcriptomics
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- dimensionality-reduction
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- ae
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- general
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license: mit
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---
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# Autoencoder (General Purpose, 8D)
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This model is part of the TRACERx Datathon 2025 transcriptomics analysis pipeline.
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## Model Details
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- **Model Type**: Autoencoder
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- **Dataset**: General Purpose
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- **Latent Dimensions**: 8
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- **Compression Mode**: transcriptome
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- **Framework**: PyTorch
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## Usage
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This model is designed to be used with the TRACERx Datathon 2025 analysis pipeline.
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It will be automatically downloaded and cached when needed.
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## Model Architecture
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- Input: Gene expression data
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- Hidden layers: [input_size, 512, 256, 128, 8]
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- Output: 8-dimensional latent representation
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- Activation: ELU with batch normalization
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## Training Data
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Trained on broader open transcriptomics datasets
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## Files
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- `autoencoder_8_latent_dims_oos_mode.pt`: Main model weights
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- `latent_df.csv`: Example latent representations (if available)
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