Repeatability of Fine-Tuning Large Language Models Illustrated Using QLoRA
Large language models (LLMs) have shown progress and promise in diverse applications ranging from the medical field to chat bots. Developing LLMs requires a large corpus of data and significant computation resources to achieve efficient learning. Foundation models (in particular LLMs) serve as the b...
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| Principais autores: | , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
IEEE
2024-01-01
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| coleção: | IEEE Access |
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| Acesso em linha: | https://ieeexplore.ieee.org/document/10700744/ |
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