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license: apache-2.0
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---
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license: apache-2.0
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language:
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datasets:
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- davzoku/moecule-finqa
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- davzoku/moecule-kyc
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- davzoku/moecule-stock-market-outlook
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---
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# 🫐🥫 trained_expert
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<p align="center">
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<img src="https://cdn-uploads.huggingface.co/production/uploads/63c51d0e72db0f638ff1eb82/yLsrUZma5WnLzJrhI6ldZ.png" width="150" height="150" alt="logo">
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</p>
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## Model Details
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This model is a domain-specific expert model for [Moecule](https://huggingface.co/collections/davzoku/moecule-67dabc6bb469dcd00ad2a7c5) family of MoE models.
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It is part of [Moecule Ingredients](https://huggingface.co/collections/davzoku/moecule-ingredients-67dac0e6210eb1d95abc6411) and all relevant expert models, LoRA adapters, and datasets can be found there.
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### Additional Information
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- QLoRA 4-bit fine-tuning with Unsloth
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- Base Model: `unsloth/llama-3-8b-Instruct`
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## The Team
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- CHOCK Wan Kee
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- Farlin Deva Binusha DEVASUGIN MERLISUGITHA
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- GOH Bao Sheng
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- Jessica LEK Si Jia
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- Sinha KHUSHI
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- TENG Kok Wai (Walter)
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## References
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- [Unsloth Tutorial](https://docs.unsloth.ai/basics/tutorial-how-to-finetune-llama-3-and-use-in-ollama)
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- [Unsloth Finetuning Colab Notebook](<https://colab.research.google.com/github/unslothai/notebooks/blob/main/nb/Llama3_(8B)-Ollama.ipynb#scrollTo=uMuVrWbjAzhc>)
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