Upload Senku-70B-Full-GGUF
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README.md
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---
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base_model: ShinojiResearch/Senku-70B-Full
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license: cc0-1.0
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language:
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- en
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library_name: peft
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pipeline_tag: text-generation
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quantized_by: brooketh
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tags:
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- generated_from_trainer
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---
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<img src="BackyardAI_Banner.png" alt="Backyard.ai" style="height: 90px; min-width: 32px; display: block; margin: auto;">
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<p style="text-align: center;"><a href="https://www.reddit.com/r/LLM_Quants/">Request Additional models at r/LLM_Quants.</a></p>
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***
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# Senku 70B
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- **Creator:** [
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- **Original:** [Senku 70B
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- **Date Created:** 2024-02-06
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- **Trained Context:**
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- **Description:** Finetune of
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***
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## What is a GGUF?
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GGUF is a large language model (LLM) format that can be split between CPU and GPU. GGUFs are compatible with applications based on llama.cpp, such as Backyard AI. Where other model formats require higher end GPUs with ample VRAM, GGUFs can be efficiently run on a wider variety of hardware.
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---
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license: cc0-1.0
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library_name: peft
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tags:
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- generated_from_trainer
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base_model: ShinojiResearch/Senku-70B-Full
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datasets:
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- Open-Orca/SlimOrca
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model_name: Senku-70B-Full-GGUF
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quantized_by: brooketh
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parameter_count: 68976648192
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---
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<img src="BackyardAI_Banner.png" alt="Backyard.ai" style="height: 90px; min-width: 32px; display: block; margin: auto;">
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<p style="text-align: center;"><a href="https://www.reddit.com/r/LLM_Quants/">Request Additional models at r/LLM_Quants.</a></p>
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***
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# Senku Full 70B
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- **Creator:** [ShinojiResearch](https://huggingface.co/ShinojiResearch/)
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- **Original:** [Senku Full 70B](https://huggingface.co/ShinojiResearch/Senku-70B-Full)
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- **Date Created:** 2024-02-06
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- **Trained Context:** 32764 tokens
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- **Description:** Finetune of miqu-70b-sf dequant of miqudev's leak of Mistral-70B (allegedly an early mistral medium). This version, using the ChatML prompt template, achieved an EQ-Bench score of 85.09.
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***
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## What is a GGUF?
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GGUF is a large language model (LLM) format that can be split between CPU and GPU. GGUFs are compatible with applications based on llama.cpp, such as Backyard AI. Where other model formats require higher end GPUs with ample VRAM, GGUFs can be efficiently run on a wider variety of hardware.
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