coder3101/Cydonia-24B-v4.3-heretic-v2
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📢 For those who interested in applying LLM for inferring iterators of data with CoT / prompts, this update might be relevant. Deligted to share the new release of the bulk-chain. This is a framework that contributes to efficient AI querying in synthetic data generation scenarios.
🌟 bulk-chain: https://github.com/nicolay-r/bulk-chain
🔑 This features the no-string framework for quierrying LLMs in various modes: sync, async and with optional support for output streaming.
📦️ In the latest 1.2.0 release, the updates on outlining API parameters for inference mode.
🌟 Integration into web: https://github.com/nicolay-r/bulk-chain-web-integration
🌟 bulk-chain: https://github.com/nicolay-r/bulk-chain
🔑 This features the no-string framework for quierrying LLMs in various modes: sync, async and with optional support for output streaming.
📦️ In the latest 1.2.0 release, the updates on outlining API parameters for inference mode.
🌟 Integration into web: https://github.com/nicolay-r/bulk-chain-web-integration
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Language Dexterity Benchmark
I am working on a new benchmark to establish human language dexterity. My hypothesis is that certain language allow for more accurate dexterous behaviour - Pointed, unambigous, and confusion-free references of parts of speech in small and large contexts. There are certain languages with high degree of accurate grammar like Sanskrit, Esperanto, and Turkish. I am native Sanskrit speaker.
I have plans to establish this benchmark and test this hypothesis across 100 langauges. I have created 25 task prompts for text, image, video and robotics manipulation. We can test langauges across multiple popular models. Here is the github link: https://github.com/ParamTatva-org/Linguistic-Dexterity-Benchmark
I am working on a new benchmark to establish human language dexterity. My hypothesis is that certain language allow for more accurate dexterous behaviour - Pointed, unambigous, and confusion-free references of parts of speech in small and large contexts. There are certain languages with high degree of accurate grammar like Sanskrit, Esperanto, and Turkish. I am native Sanskrit speaker.
I have plans to establish this benchmark and test this hypothesis across 100 langauges. I have created 25 task prompts for text, image, video and robotics manipulation. We can test langauges across multiple popular models. Here is the github link: https://github.com/ParamTatva-org/Linguistic-Dexterity-Benchmark
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