inflatebot
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Update README.md
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README.md
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---
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base_model:
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- Qwen/Qwen2.5-1.5B-Instruct
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library_name:
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tags:
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- mergekit
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- merge
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---
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# Q25-1.5-VeoLu-R2
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## Merge Details
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### Merge Method
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The following models were included in the merge:
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* /
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* /
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### Configuration
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weight: 1.0
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- layer_range: [0, 28]
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model: Qwen/Qwen2.5-1.5B-Instruct
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```
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---
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base_model:
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- Qwen/Qwen2.5-1.5B-Instruct
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library_name: peft
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tags:
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- mergekit
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- merge
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- llama-factory
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- lora
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datasets:
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- allura-org/fujin-cleaned-stage-1
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- Dampfinchen/Creative_Writing_Multiturn
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- ToastyPigeon/SpringDragon
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- allura-org/medquad_sharegpt
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- allura-org/scienceqa_sharegpt
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- Alignment-Lab-AI/orcamath-sharegpt
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---
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# Q25-1.5-VeoLu-R2
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Q25-1.5B-Veo Lu is a tiny General-Purpose Creative model, made up of a merge of bespoke finetunes on Qwen 2.5-1.5B-Instruct.
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Inspired by the success of [MN-12B-Mag Mell](https://huggingface.co/inflatebot/MN-12B-Mag-Mell-R1) and [MS-Meadowlark-22B](https://huggingface.co/allura-org/MS-Meadowlark-22B), Veo Lu was trained on a healthy, balanced diet of of Internet fiction, roleplaying, adventuring, and reasoning/general knowledge.
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The components of Veo Lu are:
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The following models were included in the merge:
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* Bard (pretrain, writing): [Fujin (Cleaned/extended Rosier)](https://huggingface.co/allura-org/fujin-cleaned-stage-1)
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* Scribe (pretrain, roleplay): [Creative Writing Multiturn](https://huggingface.co/Dampfinchen/Creative_Writing_Multiturn)
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* Cartographer (pretrain, adventuring): [SpringDragon](https://huggingface.co/ToastyPigeon/SpringDragon)
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* Alchemist (SFT, science/reasoning): [ScienceQA,](https://huggingface.co/allura-org/scienceqa_sharegpt) [MedquadQA,](https://huggingface.co/allura-org/medquad_sharegpt) [Orca Math Word Problems](https://huggingface.co/Alignment-Lab-AI/orcamath-sharegpt)
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This model is capable of carrying on a scene without going completely off the rails. That being said, it only has 1.5B parameters. So please, for the love of God, *manage your expectations.*
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Made by inflatebot.
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Special thanks to our friends at Allura, and especially to Auri, who basically held my hand through the whole process. Her effort and enthusiasm carried this project forward.
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### Configuration
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weight: 1.0
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- layer_range: [0, 28]
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model: Qwen/Qwen2.5-1.5B-Instruct
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```
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