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README.md

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+
+---
+
+base_model:
+- Qwen/Qwen2.5-1.5B-Instruct
+library_name: peft
+tags:
+- mergekit
+- merge
+- llama-factory
+- lora
+datasets:
+- allura-org/fujin-cleaned-stage-1
+- Dampfinchen/Creative_Writing_Multiturn
+- ToastyPigeon/SpringDragon
+- allura-org/medquad_sharegpt
+- allura-org/scienceqa_sharegpt
+- Alignment-Lab-AI/orcamath-sharegpt
+
+---
+
+[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory)
+
+
+# QuantFactory/Q25-1.5B-VeoLu-GGUF
+This is quantized version of [Alfitaria/Q25-1.5B-VeoLu](https://huggingface.co/Alfitaria/Q25-1.5B-VeoLu) created using llama.cpp
+
+# Original Model Card
+
+# Q25-1.5-VeoLu-R2
+![made with StableNoobAI-IterSPO in sd-webui-forge](veolu.png)
+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.
+
+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.
+
+The components of Veo Lu are:
+
+* Bard (pretrain, writing): [Fujin (Cleaned/extended Rosier)](https://huggingface.co/allura-org/fujin-cleaned-stage-1)
+* Scribe (pretrain, roleplay): [Creative Writing Multiturn](https://huggingface.co/Dampfinchen/Creative_Writing_Multiturn)
+* Cartographer (pretrain, adventuring): [SpringDragon](https://huggingface.co/ToastyPigeon/SpringDragon)
+* 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)
+
+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.*
+Since it's Qwen, use ChatML formatting. Turn the temperature down to ~0.7-0.8 and try a dash of rep-pen.
+
+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.
+```
+pip install vllm
+vllm serve Alfitaria/Q25-1.5B-VeoLu --max-model-len 16384 --max-num-seqs 1
+```
+
+Made by inflatebot.
+
+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.
+
+### Configuration
+
+The following YAML configuration was used to produce this model:
+
+```yaml
+base_model: Qwen/Qwen2.5-1.5B-Instruct
+dtype: bfloat16
+merge_method: task_arithmetic
+parameters:
+  normalize: 1.0
+slices:
+- sources:
+  - layer_range: [0, 28]
+    model: /home/asriel/AI/text/models/bard
+    parameters:
+      weight: 1.0
+  - layer_range: [0, 28]
+    model: /home/asriel/AI/text/models/scribe
+    parameters:
+      weight: 1.0
+  - layer_range: [0, 28]
+    model: /home/asriel/AI/text/models/cartographer
+    parameters:
+      weight: 1.0
+  - layer_range: [0, 28]
+    model: /home/asriel/AI/text/models/alchemist
+    parameters:
+      weight: 1.0
+  - layer_range: [0, 28]
+    model: Qwen/Qwen2.5-1.5B-Instruct
+```