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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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* 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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Since it's Qwen, use ChatML formatting. Turn the temperature down to ~0.7-0.8 and try a dash of rep-pen. |
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GGUFs coming soon, but honestly, the full-precision model is 3.5GB in size. You might wanna have a go at running this unquantized with vLLM. |
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``` |
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pip install vllm |
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vllm serve Alfitaria/Q25-1.5B-VeoLu --max-model-len 16384 --max-num-seqs 1 |
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``` |
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Made by inflatebot. |
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Special thanks to our friends at [Allura](https://huggingface.co/allura-org), and especially to [Auri](https://huggingface.co/AuriAetherwiing), 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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The following YAML configuration was used to produce this model: |
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```yaml |
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base_model: Qwen/Qwen2.5-1.5B-Instruct |
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dtype: bfloat16 |
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merge_method: task_arithmetic |
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parameters: |
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normalize: 1.0 |
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slices: |
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- sources: |
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- layer_range: [0, 28] |
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model: /home/asriel/AI/text/models/bard |
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parameters: |
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weight: 1.0 |
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- layer_range: [0, 28] |
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model: /home/asriel/AI/text/models/scribe |
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parameters: |
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weight: 1.0 |
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- layer_range: [0, 28] |
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model: /home/asriel/AI/text/models/cartographer |
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parameters: |
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weight: 1.0 |
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- layer_range: [0, 28] |
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model: /home/asriel/AI/text/models/alchemist |
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parameters: |
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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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``` |
