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maanka2/Supra-1.5-50M-Base-exp

sourceHugging Faceapache-2.0updated 3mo agoView on Hugging Face
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<h1 align="center">Supra1.5-50M Base</h1>

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

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:

SpecificationValue
ArchitectureLlamaForCausalLM
Parameters~50M
Vocabulary Size32,000
Hidden Size512
Layers12
Attention Heads8
KV Heads4
Context Length5,120 tokens
TokenizerOriginal 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