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README.md
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license: cc-by-nc-4.0
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license: cc-by-nc-4.0
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datasets:
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- tatsu-lab/alpaca
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language:
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- en
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metrics:
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- vicuna benchmark
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- wikitext2
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pipeline_tag: question-answering
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# Eluwa: A Conversational LoRA for Facebook's OPT 2.7b Architecture
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![logo](/ELUWA-LOGO.jpg "baaaaaaaaaaaa")
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Eluwa is a fine-tuned LoRA model based on Facebook's OPT 2.7b architecture and trained on the Stanford Alpaca dataset. Eluwa is designed to provide a more conversational and creative experience in question-answering mode compared to the default OPT model. The idea was that OPT was too curt (and frankly, a bit of an asshole) for a model of its size, and that we could finetune it like Alpaca did to Llama.
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It worked! Based on very limited testing, it's about halfway to GPT 3.5. Response times are fast: on my GTX 1080ti + Ryzen 3600,it generates between 1.14 tokens/s and 3.77 tokens/s.
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