---
license: mit
tags:
- debil
datasets:
- roneneldan/TinyStories
---
# 🚀 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:


![image](https://cdn-uploads.huggingface.co/production/uploads/6a1d885bbd8b36b69d8a8727/q91f49Lm3Ny8XfCvhVFTP.png)