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chore(model gallery): add 14b-qwen2.5-freya-x1 (#4566)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
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@ -2849,6 +2849,30 @@
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- filename: Dolphin3.0-Qwen2.5-3b-Q4_K_M.gguf
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sha256: 0cb1908c5f444e1dc2c5b5619d62ac4957a22ad39cd42f2d0b48e2d8b1c358ab
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uri: huggingface://bartowski/Dolphin3.0-Qwen2.5-3b-GGUF/Dolphin3.0-Qwen2.5-3b-Q4_K_M.gguf
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- !!merge <<: *qwen25
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name: "14b-qwen2.5-freya-x1"
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icon: https://huggingface.co/Sao10K/14B-Qwen2.5-Freya-x1/resolve/main/sad.png
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urls:
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- https://huggingface.co/Sao10K/14B-Qwen2.5-Freya-x1
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- https://huggingface.co/DevQuasar/Sao10K.14B-Qwen2.5-Freya-x1-GGUF
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description: |
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I decided to mess around with training methods again, considering the re-emegence of methods like multi-step training. Some people began doing it again, and so, why not? Inspired by AshhLimaRP's methology but done it my way.
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Freya-S1
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LoRA Trained on ~1.1GB of literature and raw text over Qwen 2.5's base model.
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Cleaned text and literature as best as I could, still, may have had issues here and there.
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Freya-S2
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The first LoRA was applied over Qwen 2.5 Instruct, then I trained on top of that.
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Reduced LoRA rank because it's mainly instruct and other details I won't get into.
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overrides:
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parameters:
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model: Sao10K.14B-Qwen2.5-Freya-x1.Q4_K_M.gguf
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files:
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- filename: Sao10K.14B-Qwen2.5-Freya-x1.Q4_K_M.gguf
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sha256: 790953e2ffccf2f730d52072f300fba9d1549c7762f5127b2014cdc82204b509
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uri: huggingface://DevQuasar/Sao10K.14B-Qwen2.5-Freya-x1-GGUF/Sao10K.14B-Qwen2.5-Freya-x1.Q4_K_M.gguf
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- &smollm
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## SmolLM
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url: "github:mudler/LocalAI/gallery/chatml.yaml@master"
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