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