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LongNet-Char-Shakespeare

A character-level LongNet language model trained on the full Tiny Shakespeare dataset (~1.1M characters).

Architecture: LongNet (dilated attention Transformer) – supports theoretically up to 1B tokens context length
Base model: Custom from-scratch implementation (no transformers library dependency)
Parameters: ~6.3M
Context length used in training: 8192 tokens (character-level)
Training data: Tiny Shakespeare (full text of Shakespeare's plays)
Tokenizer: Character-level (65 tokens)
Training steps: [insert your final step count, e.g. 5000+]
Hardware: Single GPU (RTX/equivalent with 4GB VRAM)

from longnet_model import LongNetLM

model = LongNetLM.from_pretrained("your-username/longnet-char-shakespeare")
model.eval()