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README.md
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license: other
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license_name: mrl
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language:
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- en
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- zh
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base_model: allura-org/Bigger-Body-8b
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library_name: transformers
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tags:
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- axolotl
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- roleplay
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- conversational
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- chat
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- llama-cpp
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- gguf-my-repo
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---
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# Triangle104/Bigger-Body-8b-Q8_0-GGUF
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This model was converted to GGUF format from [`allura-org/Bigger-Body-8b`](https://huggingface.co/allura-org/Bigger-Body-8b) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/allura-org/Bigger-Body-8b) for more details on the model.
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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---
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license: other
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license_name: mrl
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language:
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- en
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- zh
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base_model: allura-org/Bigger-Body-8b
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library_name: transformers
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tags:
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- axolotl
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- roleplay
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- conversational
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- chat
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- llama-cpp
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- gguf-my-repo
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---
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# Triangle104/Bigger-Body-8b-Q8_0-GGUF
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This model was converted to GGUF format from [`allura-org/Bigger-Body-8b`](https://huggingface.co/allura-org/Bigger-Body-8b) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/allura-org/Bigger-Body-8b) for more details on the model.
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---
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A roleplay-focused pseudo full-finetune of Ministral Instruct 2410. The successor to the Ink series.
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Dataset
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The Bigger Body (referred to as Ink v2.1, because that's still the
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internal name) mix is absolutely disgusting. It's even more cursed than
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the original Ink mix.
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(Public) Original Datasets
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-Fizzarolli/limarp-processed
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-Norquinal/OpenCAI - two_users split
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-allura-org/Celeste1.x-data-mixture
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-mapsila/PIPPA-ShareGPT-formatted-named
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allenai/tulu-3-sft-personas-instruction-following
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-readmehay/medical-01-reasoning-SFT-json
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-LooksJuicy/ruozhiba
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-shibing624/roleplay-zh-sharegpt-gpt4-data
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-CausalLM/Retrieval-SFT-Chat
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-ToastyPigeon/fujin-filtered-instruct
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Recommended Settings
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-
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Chat template: Mistral v7-tekken (NOT v3-tekken !!!! the main difference is that v7 has specific [SYSTEM_PROMPT] and [/SYSTEM_PROMPT] tags)
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Recommended samplers (not the be-all-end-all, try some on your own!):
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I have literally no idea. you're on your own.
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Hyperparams
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General
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Epochs = 2
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LR = 2e-6
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LR Scheduler = Cosine
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Optimizer = Apollo-mini
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Optimizer target modules = all_linear
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Effective batch size = 16
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Weight Decay = 0.01
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Warmup steps = 50
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Total steps = 920
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Credits
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Humongous thanks to the people who created the data.
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Big thanks to all Allura members for testing and emotional support ilya /platonic
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---
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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