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anlp-assignment1-cipher-decoder
vanshnawander/anlp-assignment1-cipher-decoder
anlp-assignment1-cipher-decoder is a machine learning model from vanshnawander. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for pytorch. The card lists the license as mit.
Best inference checkpoints for five encoder-decoder configurations trained to reconstruct plaintext from binary ciphertext:
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Updated Sep 2, 2026
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At a glance
- Library
- pytorch
- License
- mit
- Access
- Public
- Created
- Sep 2, 2026
- Updated
- Sep 2, 2026
- SHA
- 505f5706
Model card
From the Hugging Face model README
ANLP Assignment 1: Cipher-to-Text Models
Best inference checkpoints for five encoder-decoder configurations trained to reconstruct plaintext from binary ciphertext:
- C1: Base Transformer
- C2: Rotary positional embeddings (RoPE)
- C3: Grouped-query attention (GQA)
- C4: RMSNorm
- C5: Tokenizer-free byte latent transformer (BLT)
C1--C4 use the included byte-level BPE tokenizer. C5 consumes cipher bytes directly and uses entropy-based patches. Each checkpoint contains the model state and the exact architecture configuration used during training.
Training curves and evaluation results are available in the Weights & Biases report. Try the models in the Gradio demo.
- Library
- pytorch
- License
- mit
- Created
- Sep 2, 2026
- Updated
- Sep 2, 2026