(3/3) Cerebras CEO, Andrew Feldman, says “We believe this strategic partnership can add a meaningful amount of AI compute to the worldwide inventory. This type of partnership, and the opportunity to collaborate to change the AI landscape, is why entrepreneurs start companies."
@cerebras
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G42 and Cerebras Build Infrastructure for Massive LLM Training
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(1/3) "G42 and Cerebras will soon be in the bigtime when it comes to having infrastructure that can train very humungous large language models," writes @TDaytonPM from
@TheNextPlatform Read the article here:
https://
lnkd.in/gXPjdgks -
BTLM-3B Outperforms Larger Models in Real-World Deployments
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People are ripping out their 3B and even 7B models and dropping in BTLM-3B. It's that good!
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Cerebras Opentensor Host AMA on BTLM-3B-8K Model
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Reminder that at 10:00 am PT today, Cerebras and Opentensor will host an AMA on our Discord server to talk about BTLM-3B-8K. Come to ask questions, engage in a discussion, or simply enjoy the conversations! Join our Discord here: https://
hubs.li/Q01ZhwD80 -
LLaMA 2 and BTLM: Best Models by Parameter Size
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Need best 7B-70B models? Use LLaMA 2.
Need best 3B model? Use BTLM.
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Cerebras-GPT: First Open-Source Compute-Optimal Models
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Cerebras-GPT – Deploying the first open-source compute-optimal models – https://
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Sparse-IFT: Larger Sparse Models with Higher Accuracy
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Sparse-IFT – Creating larger sparse models with higher accuracy at the same compute – https://
hubs.li/Q01Z9vCZ0 -
VSL: Variable Sequence Lengths for Cost-Effective Long Context
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VSL – Utilizing variable sequence lengths to achieve longer sequences at lower cost – https://
hubs.li/Q01Z9jxc0 -
SparseGPT: Sparsifying LLMs for efficient inference
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SparseGPT – Sparsifying LLMs for efficient inference – https://
hubs.li/Q01Z9ysx0 -
Sparse models match dense accuracy with fewer flops
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SPDF – Matching the downstream accuracy of a dense model with a sparse model using fewer flops – https://
hubs.li/Q01Z9v0G0