A specialized question-answering model fine-tuned on cannabis science literature. This model is based on IBM’s Granite 3.0-8B Instruct and has been fine-tuned using QLoRA on 161,170 cannabis science Q&A pairs derived from peer-reviewed research papers. This model specializes in answering scientific questions about cannabis, including topics in chemistry, biology, pharmacology, extraction methods, cultivation, and medical applications. It has been trained to provide accurate, research-backed responses based on peer-reviewed cannabis science literature. — Developed by: Kellan Finney — Funded by: Eighth Revolution — Model type: Causal Language Model (Fine-tuned with QLoRA) — Language(s): English — License: Apache 2.0 — Base model: ibm-granite/granite-3.0-8b-instruct — Training method: QLoRA (Quantized Low-Rank Adaptation) — Repository: https://github.com/KellanFinney/CannaLoRA — Dataset: Cannabis Science QA Dataset — Base Model:** IBM Granite 3.0-8B Instruct — Scientific Q&A: Answer questions about cannabis chemistry, biology
Модальности:
Генерация текста
Области применения:
Ответы на вопросы Медицина Биология Химия
Задача: Генерация текста
Автор: KellanF89
Теги: peft, gguf, cannabis, science, medical, biology, chemistry, question-answering
Лайков: 4 | Загрузок: 28
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
