🚀 debil-1.5-completion

A lightweight base language model with 46.5M parameters, trained for raw text completion.

Unlike instruction-tuned or chat models, debil-1.5-completion has not been trained on dialogue or instruction-following datasets. It is a pure completion model designed to continue text based on the provided context.

Technical Specifications:

• Total Parameters: 46,538,400 (~46.5M)
• Vocabulary Size: 50,257
• Embedding Dimensions: 480
• Hidden Layers: 8
• Attention Heads: 8
• Head Dimension: 60
• Model Type: Causal Language Model
• Training Objective: Next-token prediction

Model Behavior:

The model is trained to predict the next token in a sequence rather than to follow conversational instructions.

For example, given:

The quick brown fox

the model attempts to continue the sequence with what it predicts is the most likely continuation.

It does not have a dedicated chat format or instruction-tuning layer.

Benchmark Results: