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BLT Trainer

A pure functional PyTorch implementation of a 96-layer Byte Latent Transformer (BLT) with Muon + ScheduleFreeAdamW optimization and weighted multi-corpus datamix.

Features

  • Byte Latent Architecture: Vectorized entropy/surprise-based dynamic byte patching and cross-attention pooling.
  • Downloaded Datamix: Datasets are downloaded and locally cached to disk using Apache Arrow memory-mapping to completely prevent Hugging Face API rate-limiting during training.
  • Weighted Multi-Corpus Sampling:
    • DCLM Baseline (mlfoundations/dclm-baseline-1.0)
    • FLAN Collection (Muennighoff/flan)
    • Wikipedia QA (microsoft/wiki_qa)
    • OpenWebMath Reasoning (open-web-math/open-web-math)
    • Ubuntu Dialogue QA (sedthh/ubuntu_dialogue_qa)
  • Advanced Logging: Real-time throughput reporting with TPS (Tokens Per Second), Tokens Processed, step latency, and ETA.
  • Dual Optimizer Partitioning: Muon optimizer for 2D hidden projection matrices and Schedule-Free AdamW for 1D embeddings and norm weights.
  • Cut Cross-Entropy: Chunked sequence loss computation to eliminate peak VRAM spikes from materializing large vocabulary logits.

Installation

pip install -e .

Usage

Run Training

blt-train --batch-size 8 --block-size 512 --steps 10000 --device cuda

CLI Options

Flag Type Default Description
--steps int 10000 Total training steps
--batch-size int 8 Batch size per step
--block-size int 512 Byte context length
--streaming flag False Stream from Hugging Face instead of downloading locally (default: False, downloaded)
--cache-dir str None Custom directory to cache downloaded datasets
--log-interval int 10 Frequency of progress logs in steps
--device str cuda (if available) else cpu Execution device
--compile flag False Enable torch.compile kernel fusion
--lr-muon float 0.02 Learning rate for Muon optimizer
--lr-adam float 1e-3 Learning rate for Schedule-Free AdamW

Logging Output

Logs include step progress, loss, Tokens Per Second (TPS), Tokens Processed, step latency, and estimated time of arrival (ETA):

Step 00010/10000 (  0.1%) | Loss: 6.4215 | TPS:  14,250.3 | Tokens: 40,960 (40.96K) | Step Time:   35.9ms | ETA: 00:05:55 | VRAM: 3.45GB
Step 00020/10000 (  0.2%) | Loss: 6.1023 | TPS:  14,310.0 | Tokens: 81,920 (81.92K) | Step Time:   35.7ms | ETA: 00:05:52 | VRAM: 3.45GB

Metadata

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