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--- |
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license: mit |
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tags: |
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- llama-2 |
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- mlx |
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language: |
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- fr |
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- el |
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library_name: mlx |
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pipeline_tag: text-generation |
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--- |
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<img src="https://l0d0v1c.github.io/notes/medias/greeks.jpg"/> |
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# An Ancient Greek/French Model for RAG |
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* based on mistralai/Mistral-7B-v0.1 |
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* Trained on [1] (and automated translation by GTP4) and [2] |
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* For RAG [3] |
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* may produce unaccurate results in translation |
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* https://www.diogenial.com https://rd-mediation.com |
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* Framework MLX Apple Silicon [4] |
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## Example |
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<code>La traduction de Φασὶ δὲ καὶ Ἀλέξανδρον εἰπεῖν ὡς εἴπερ Ἀλέξανδρος μὴ ἐγεγόνει, ἐθελῆσαι ἂν Διογένης γενέσθαι est: |
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Diogène dit que si Alexandre avait été moins ambitieux, il aurait bien voulu être Diogène.</code> |
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(imprécise: On assure qu’Alexandre disait que s’il n’était pas Alexandre il voudrait être Diogène. selon [5]) |
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## Use |
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<code>from mlx_lm import load, generate |
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model, tokenizer = load("RANDMEDIATION/DiogenialRAG") |
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response = generate(model, tokenizer, prompt=input("prompt:"), verbose=True,max_tokens=256,temp=0.8)</code> |
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## References |
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[1] Giannantoni, Gabriele, éd. Socratis et Socraticorum reliquiae. Elenchos 18. Book V. Naples, Italy: Bibliopolis, 1990. |
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[2] https://tatoeba.org/fr/sentences/show_all_in/grc/none |
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[3] Lewis, Patrick, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, et al. « Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks ». In Advances in Neural Information Processing Systems, édité par H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan, et H. Lin, 33:9459‑74. Curran Associates, Inc., 2020. https://proceedings.neurips.cc/paper_files/paper/2020/file/6b493230205f780e1bc26945df7481e5-Paper.pdf. |
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[4] Hannun, Awni, Jagrit Digani, Angelos Katharopoulos, et Ronan Collobert. « MLX: Efficient and flexible machine learning on Apple silicon », 2023. https://github.com/ml-explore. |
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[5] https://remacle.org/bloodwolf/philosophes/laerce/6diogene1.htm |
