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  - H-D-T/Buzz
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  language:
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  - en
 
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  ---
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  # Buzz-8b-Large-GGUF
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  We intend to focus on *updating* and improving the performance of these models, and surrounding open sourced infrastructure. Our next effort will focus on context and implementing the research currently being conducted by [Wing-Lian](https://github.com/winglian), the lead developer of the [Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) training framework that underpins these experiments. We encourage the community to explore Wing-Lian's work, such as the [Llama-3-8b-64k-PoSE](https://huggingface.co/winglian/Llama-3-8b-64k-PoSE) and [llama-3-8b-256k-PoSE](https://huggingface.co/winglian/llama-3-8b-256k-PoSE) models, which showcase the potential for further advancements in language modeling.
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- Buzz hopes to be a proof of concept, and a toolkit to demonstrate and enable the community in the pursuit of efficient and effective locally run, personally owned, language models. Through collaboration with [Hive Digital Technologies](https://hivedigitaltechnologies.com/) who have enabled us to perform this research, we have demonstrated the immense potential for model reuse and optimization.
 
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  - H-D-T/Buzz
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  language:
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  - en
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+ pipeline_tag: text-generation
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  ---
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  # Buzz-8b-Large-GGUF
 
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  We intend to focus on *updating* and improving the performance of these models, and surrounding open sourced infrastructure. Our next effort will focus on context and implementing the research currently being conducted by [Wing-Lian](https://github.com/winglian), the lead developer of the [Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) training framework that underpins these experiments. We encourage the community to explore Wing-Lian's work, such as the [Llama-3-8b-64k-PoSE](https://huggingface.co/winglian/Llama-3-8b-64k-PoSE) and [llama-3-8b-256k-PoSE](https://huggingface.co/winglian/llama-3-8b-256k-PoSE) models, which showcase the potential for further advancements in language modeling.
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+ Buzz hopes to be a proof of concept, and a toolkit to demonstrate and enable the community in the pursuit of efficient and effective locally run, personally owned, language models. Through collaboration with [Hive Digital Technologies](https://hivedigitaltechnologies.com/) who have enabled us to perform this research, we have demonstrated the immense potential for model reuse and optimization.