Yi-Large can process and comprehend larger bodies of text with an extended context length of 32K tokens, ensuring high-performance and speed when handling large amounts of data. Test out the model today on the Fireworks AI Playground: https://
fireworks.ai/models/firewor
ks/yi-large
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LLMS
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Yi-Large Model Now Available with 32K Token Context Length
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Fine-Tuned Open-Source Models Outperform GPT-4o-mini on SLM Leaderboard
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We updated our fine-tuned #SLM leaderboard to include #GPT4o-mini. So, who's the champ? Let's hear it for open-source and #llama3! Our fine-tuned open-source models dominated—outperforming #GPT4 and GPT-4o-mini on 80% of tasks.
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Evaluating Gemini Code Assist with Large Context Windows
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Finally got into Gemini code assist with 1M today My question all the time is how to realise if it hallucinates or not when it deals with close to 1M token files
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ChatGPT Launches GPT-4o Mini to Replace 3.5 Turbo
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Right on cue with our comments on smaller models earlier this week, @ChatGPTapp has released GPT-4o mini to replace 3.5 Turbo. This will give users access to a model that can accomplish many tasks for far cheaper! Are you a paid ChatGPT user or on the free plan? #ChatGPT #AI
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OpenAI GPT-4o Mini and Latest AI Model Releases Today
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Top stories in AI today: -OpenAI debuts new GPT-4o mini model
-Mistral and Nvidia drop small AI powerhouse
-Automate your content creation workflow
-Groq’s new AI models surge up leaderboard
-5 new AI tools & 4 new AI jobs Read more: http://
therundown.ai/p/openais-new-
mini-model
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GPT-6 completes training on Azure infrastructure
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Sabíamos que esto iba a ocurrir. GPT-6 ha terminado su entrenamiento en la infraestructura de Azure…
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GPT-4o Voice Mode Alpha Launch This Month
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La alpha del modo voz de GPT-4o empieza este mes. Quiénes accederán y cuántas "semanas" hasta tener acceso general son incógnitas por resolver.
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Models must get larger to refactor entangled thinking and knowledge
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“The reason doing better is hard is because demonstrations of thinking are ‘entangled’ with knowledge, in the training data. Therefore, the models have to first get larger before they can get smaller, because we need their (automated) help to refactor and mold the training data
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Yi-Large Demonstrates Excellence in Logic and Reasoning Challenges
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Check out Yi-Large in action as it excels in some of the toughest logic and reasoning challenges Thank you to @MatthewBerman for this great validation! What other challenges would you like to see Yi-Large take on? Let us know Watch the full video:
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Later examples inconsistent with 9/11 cause; tokenization not special
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later examples are inconsistent with the primary cause being 9/11-related e.g. 2525.11 – 2525.9 = 0.21 Also the tokenization isn’t special for 9.11 — you can check using https://
platform.openai.com/tokenizer