The hybrid Jamba architecture enables Jamba-1.5 models to reach excellent throughput and latency, especially at long contexts. With the same hardware, Jamba-1.5 models are the fastest across the board (in the image: 2xA100 80GB GPUs for Mini, 8xA100 80GB GPUs for Large). 2/7
LLMS
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Jamba-1.5 Whitepaper Released: Hybrid SSM-Transformer Models
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Jamba-1.5 whitepaper is out!
The whitepaper details the architecture, training schemes, novelties and in-depth evaluations of our new long context hybrid SSM-Transformer models – Jamba-1.5-Large and Jamba-1.5-Mini. Arxiv: https://
arxiv.org/abs/2408.12570 Here are some highlights and -
Phi-3.5: Microsoft Introduces Its New Generation of SLMs
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[#Article] Phi-3.5: @Microsoft presents the latest generation of its SLMs, optimized for specific tasks https://actuia.com/actualite/phi-3-5-microsoft-presente-la-derniere-generation-de-ses-slm-optimisee-pour-des-taches-specifiques/
… #AI #ArtificialIntelligence -
LM Studio v0.3 Released with Improved User Interface
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Also enjoying the v0.3 of @LMStudioAI
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Hallucinations Leaderboard: Measuring LLM Reliability and Accuracy
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If you want to learn more hallucinations in LLM, I recommend the hallucinations leaderboard (cc @clefourrier
): https://
huggingface.co/spaces/halluci
nations-leaderboard/leaderboard
… It also comes with a nice paper from Hong et al. https://
arxiv.org/abs/2404.05904 -
Claude Family Models Excel with Strong Alignment Safety Measures
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The Claude family from @AnthropicAI is really good at it: Claude 3.5 Sonnet, 3 Opus & Haiku all succeed. It feels like a heavy alignment stage with refusals is part of the explanation.
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GPT-4 Outperforms 4o Versions in Question Answering
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The old GPT-4 also correctly answers the question, while the 4o versions fail.
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Gemma 2 Model Size Performance Variations and Arena Optimization
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For example, Gemma 2 2B IT answers correctly while the 9B version fails. I'd imagine that models optimized for @lmsysorg Chatbot Arena would perform worse, but that's not always the case.
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AI Model Hallucinations: Size Doesn’t Guarantee Factual Accuracy
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The "Indigo Sock Game" doesn't exist but most models will hallucinate it for you. Factuality hallucinations are fascinating because they often behave in unexpected ways. You'd think bigger models would perform better, but that's not necessarily true.
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Open-Source LLMs: Unsung Pioneer in AI Evolution
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Doesn't get enough credit but IMO paved the way for open-source LLMs!