slm-125m-base
A 125.8M-parameter Llama-architecture language model, trained from scratch on a legal/financial corpus.
Data
Trained on ~2.19B tokens: US case law (~40%), SEC filings (~40%), and FineWeb-Edu web text (~20%). See the project's Agent_brief.md for the full data pipeline (cleaning, dedup, decontamination).
Architecture
- vocab_size: 16384
- hidden_size: 768
- num_hidden_layers: 12
- num_attention_heads: 12
- max_position_embeddings: 1024
Training
Pretrained on 8xH100 via Modal, budget-capped at $40.
