SupraLabs/Supra1.5-50M-Base-exp

<h1 align="center">Supra1.5-50M Base</h1>

<p align="center"> Continued Pretraining • 50M Parameters • 5K Context </p>

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:

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

Credit goes to @QyrouNnet-AI