---
license: apache-2.0
datasets:
- PleIAs/common_corpus
language:
- en
- fr
- es
- de
- it
- la
- nl
- pl
---
<div style="text-align: center;">
  <img src="https://raw.githubusercontent.com/Pleias/logos/d6152d7943905da32a1e04fdfd7708ed9c7eed5e/PleIAs%201_0%20Full%20Logo%20(Black).png" style="width: 80%; margin: 0 auto; display: inline-block;"/>
</div>

**Pleias-nano-1b-Preview** is an early preview of a 1.21 billion parameters base model trained by [Pleias](https://huggingface.co/PleIAs) with [Tracto AI](https://tracto.ai/) on [Common Corpus](https://huggingface.co/datasets/PleIAs/common_corpus).

Like all the base and specialized models from Pleias, Pleias-nano-1b-Preview has only been trained on open data out of copyright (public domain) or under a permissible license.

## Description
Pleias-nano-1b-Preview is a transformer base model, entirely pretrained from scratch, using an architecture similar to Llama/GPT-Neox for easier deployment/inference.

It includes the following features, that would apply to any responsibly trained variant:
* Only trained on open data under a permissible license and in compliance with the European AI Act. By design, all Pleias model are unable to output copyrighted content.
* Extensive multilingual support for main European languages.
* A new tokenizer designed for enhanced document processing tasks and better multilingual support.
* Extremely low level of toxicity and problematic content.

Pleias-nano-1b-Preview has demonstrated unusual abilities for multilingual generation in its size range. Fully supported languages include English, French, Spanish, German, Italian, Dutch, Latin and Portuguese. 

Given its size, Pleias-nano-1b-Preview can run on CPU without any compression loss. We provide a first GGUF variant as part of our release.

## Recommended use
As a base model, Pleias-nano-1b-Preview is only able to run continuation prompts.

Text generation is currently able to support a range of creative writing tasks in multiple European languages. For more consistent results we recommend using a low or null temperature with a slight repetition penalty (1.2).

Pleias-nano-1b-Preview has been successfully adapted for continuous pretraining and full-fine-tuning on document processing tasks such as RAG, translation or OCR correction. Given the small size of the model we do not recommend fine-tuning methods based on LORA.

## Example


## Training
Pleias-nano-1b-Preview was fully pretrained on TractoAI on ISEG GPU cluster by Nebius AI on 192 h100s for 5 days. Pretraining code relied on [the fork of Nanotron developed by TractoAI](https://github.com/tractoai/nanotron). We provide the complete settings as a yaml file as part of our release. 

Training schedule includes 518,000 steps (batch size 1,024) on over three epochs (nearly 5 trillions tokens):
* A lightly filtered version of Common Corpus (1.6 trillion tokens)
* A filtered and enhanced version of Common Corpus (1,086,324,736,000 tokens).
* A repeat of the previous set.

## Update
Pleias-nano-1b-Preview is currently released as an early preview.

The model will undergo several more round of post-training to enhance reasoning capacities and fine-tunability as well as in anticipation of a generalist instruct version.