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ae_tracerx_64d
jruffle/ae_tracerx_64d
ae_tracerx_64d is a machine learning model from jruffle. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
This model is part of the TRACERx Datathon 2025 transcriptomics analysis pipeline.
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Public
Updated Jan 8, 2026
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At a glance
- License
- mit
- Access
- Public
- Created
- Aug 27, 2025
- Updated
- Jan 8, 2026
- SHA
- a83721ed
Model card
From the Hugging Face model README
Autoencoder (TRACERx-focused, 64D)
This model is part of the TRACERx Datathon 2025 transcriptomics analysis pipeline.
Model Details
- Model Type: Autoencoder
- Dataset: TRACERx-focused
- Latent Dimensions: 64
- Compression Mode: samples
- Framework: PyTorch
Usage
This model is designed to be used with the TRACERx Datathon 2025 analysis pipeline. It will be automatically downloaded and cached when needed.
Model Architecture
- Input: Gene expression data
- Hidden layers: [input_size, 512, 256, 128, 64]
- Output: 64-dimensional latent representation
- Activation: ELU with batch normalization
Training Data
Trained exclusively on TRACERx open dataset
Files
autoencoder_64_latent_dims_oos_mode.pt: Main model weightslatent_df.csv: Example latent representations (if available)
- License
- mit
- Created
- Aug 27, 2025
- Updated
- Jan 8, 2026