Continued Pretraining • 50M Parameters • 5K Context
Supra-1.5-Base-EXP
Supra-1.5-50M-Base-exp is a continued-pretrained 50M parameter Llama-style base
model derived from SupraLabs/Supra-50M-Base. The target update expands the
usable context window from 1,024 tokens to 5,120 tokens using RoPE scaling and
full-weight continued pretraining.
Architecture
The model keeps the original Supra-50M architecture and tokenizer:
Specification
Value
Architecture
LlamaForCausalLM
Parameters
~50M
Vocabulary Size
32,000
Hidden Size
512
Layers
12
Attention Heads
8
KV Heads
4
Context Length
5,120 tokens
Tokenizer
Original Supra byte-level BPE tokenizer
Continued Pretraining Objective
This is CPT, not instruction fine-tuning. Training uses packed raw text with
standard causal language-modeling loss:
labels = input_ids
all non-pad tokens are trained
no response-only masking
no system/user/assistant masking
no LoRA adapters in the default run
Data Mix
The current local training mix prepared for this run is:
3,000,000,062 CPT tokens
30% Tool Calling
30% ChatML Conversations
25% Factual Text (articles, essays, blogs)
15% Math & Logic Questions
Intended Use
Supervised Fine-Tuning (SFT) and Reinforcement Learning
