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---
datasets:
- oscar-corpus/OSCAR-2301
language:
- it
tags:
- ipt-125m
---
# IPT-125m (WIP)
IPT-125m is a decoder-style transformer pretrained from scratch on 4.36 billion tokens of Italian text from the [OSCAR-2301](https://huggingface.co/datasets/oscar-corpus/OSCAR-2301) dataset.
If you like this project, consider supporting me with a cup of coffee! 🤖✨🌞
[](https://bmc.link/edoardofederici)
## How to Use
This model is best used with the Hugging Face `transformers` library for training and finetuning.
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("efederici/ipt-125m", trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained("efederici/ipt-125m")
```
## Model Description
The architecture is a modification of a standard decoder-only transformer.
| Hyperparameter | Value |
|----------------|-------|
|n_parameters | 125M |
|n_layers | 12 |
| n_heads | 12 |
| d_model | 768 |
| vocab size | 50432 |
| sequence length | 2048 |
|