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README.md
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<div style="text-align: center; display: flex; flex-direction: column; align-items: center;">
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<img src="https://
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</div>
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# Model Card for Minerva-7B-
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Minerva is the first family of **LLMs pretrained from scratch on Italian** developed by [Sapienza NLP](https://nlp.uniroma1.it)
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in collaboration with [Future Artificial Intelligence Research (FAIR)](https://fondazione-fair.it/) and [CINECA](https://www.cineca.it/).
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* [Minerva-1B-base-v1.0](https://huggingface.co/sapienzanlp/Minerva-1B-base-v1.0)
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* [Minerva-3B-base-v1.0](https://huggingface.co/sapienzanlp/Minerva-3B-base-v1.0)
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* [Minerva-7B-base-v1.0](https://huggingface.co/sapienzanlp/Minerva-7B-base-v1.0-1110)
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* [Minerva-7B-
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* [Minerva-7B-base-v1.0-dpo](https://huggingface.co/sapienzanlp/Minerva-7B-cpt-v1.0-mixed_recipe7-3epochs-safety-handcraft-DPO-alert-uf-evol-temp)
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## 🚨⚠️🚨 Bias, Risks, and Limitations 🚨⚠️🚨
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import transformers
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import torch
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model_id = "sapienzanlp/Minerva-7B-
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# Initialize the pipeline.
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pipeline = transformers.pipeline(
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---
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<div style="text-align: center; display: flex; flex-direction: column; align-items: center;">
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<img src="https://huggingface.co/sapienzanlp/Minerva-7B-instruct-v1.0/resolve/main/minerva-logo.png" style="max-width: 550px; height: auto;">
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</div>
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# Model Card for Minerva-7B-instruct-v1.0
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Minerva is the first family of **LLMs pretrained from scratch on Italian** developed by [Sapienza NLP](https://nlp.uniroma1.it)
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in collaboration with [Future Artificial Intelligence Research (FAIR)](https://fondazione-fair.it/) and [CINECA](https://www.cineca.it/).
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* [Minerva-1B-base-v1.0](https://huggingface.co/sapienzanlp/Minerva-1B-base-v1.0)
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* [Minerva-3B-base-v1.0](https://huggingface.co/sapienzanlp/Minerva-3B-base-v1.0)
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* [Minerva-7B-base-v1.0](https://huggingface.co/sapienzanlp/Minerva-7B-base-v1.0-1110)
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* [Minerva-7B-instruct-v1.0](https://huggingface.co/sapienzanlp/Minerva-7B-instruct-v1.0)
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## 🚨⚠️🚨 Bias, Risks, and Limitations 🚨⚠️🚨
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import transformers
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import torch
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model_id = "sapienzanlp/Minerva-7B-instruct-v1.0"
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# Initialize the pipeline.
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pipeline = transformers.pipeline(
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