![llamantino3_anita](https://cdn-uploads.huggingface.co/production/uploads/5df8bb21da6d0311fd3d540f/xL6Ax1I34qfC4VPKEFA6Z.png)
"Built with Meta Llama 3".
LLaMAntino-3-ANITA-8B-Inst-DPO-ITA is a model of the LLaMAntino - Large Language Models family. The model is an instruction-tuned version of Meta-Llama-3-8b-instruct (a fine-tuned LLaMA 3 model). This model version aims to be the a Multilingual Model ๐ (EN ๐บ๐ธ + ITA๐ฎ๐น) to further fine-tuning on Specific Tasks in Italian.
The ๐ANITA project๐ *(Advanced Natural-based interaction for the ITAlian language)* wants to provide Italian NLP researchers with an improved model for the Italian Language ๐ฎ๐น use cases.
Model Details
https://github.com/marcopoli/LLaMAntino-3-ANITA
- Full Model: LaMAntino-3-ANITA-8B-Inst-DPO-ITA
- LLaMA.cpp - F16 model
- LLaMA.cpp - Q8_0 model
- LLaMA.cpp - Q4_K_M model
- LLaMA.cpp - Q2_K model
Specifications
- Model developers:
Ph.D. Marco Polignano - University of Bari Aldo Moro, Italy
SWAP Research Group - Variations: The model release has been supervised fine-tuning (SFT) using QLoRA 4bit, on instruction-based datasets. DPO approach over the mlabonne/orpo-dpo-mix-40k dataset is used to align with human preferences for helpfulness and safety.
- Input: Models input text only.
- Language: Multilingual ๐ + Italian ๐ฎ๐น
- Output: Models generate text and code only.
- Model Architecture: Llama 3 architecture.
- Context length: 8K, 8192.
- Library Used: LLaMA.cpp
Prompt Template
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{ SYS Prompt }<|eot_id|><|start_header_id|>user<|end_header_id|>
{ USER Prompt }<|eot_id|><|start_header_id|>assistant<|end_header_id|>
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LLaMA.cpp
![](https://user-images.githubusercontent.com/1991296/230134379-7181e485-c521-4d23-a0d6-f7b3b61ba524.png)
LLaMA.cpp, a great tool that helps us easily Quantize your model in GGUF format.
Citation instructions
@misc{polignano2024advanced,
title={Advanced Natural-based interaction for the ITAlian language: LLaMAntino-3-ANITA},
author={Marco Polignano and Pierpaolo Basile and Giovanni Semeraro},
year={2024},
eprint={2405.07101},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
@misc{basile2023llamantino,
title={LLaMAntino: LLaMA 2 Models for Effective Text Generation in Italian Language},
author={Pierpaolo Basile and Elio Musacchio and Marco Polignano and Lucia Siciliani and Giuseppe Fiameni and Giovanni Semeraro},
year={2023},
eprint={2312.09993},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
@article{llama3modelcard,
title={Llama 3 Model Card},
author={AI@Meta},
year={2024},
url = {https://github.com/meta-llama/llama3/blob/main/MODEL_CARD.md}
}
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