Sparse-IFT – Creating larger sparse models with higher accuracy at the same compute – https://
hubs.li/Q01Z9vCZ0
LLMS
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Sparse-IFT: Larger Sparse Models with Higher Accuracy
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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 -
Visual Foundation Models: Architectures, Training, and Prompting Survey
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Foundational Models Defining a New Era in Vision: A Survey and Outlook A comprehensive survey of visual foundation models. Covers emerging architectures(for vision+other modalities), training objectives, pre-training datasets, fine-tuning mechanisms, and the common prompting
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LLM Text Adversarial Problems Easier Than Vision Recognition
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I do agree that trying to solve this within LLM will be hard. But the problem seems easier to solve in practice than vision, unless people come up with a way to make an adversarial string that reads like natural language
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Adversarial Examples in Vision vs Language Models Vulnerability
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Adversarial examples have been hard to solve in vision mainly because it was imperceptible to humans and added adv noise is hard to remove. Looking at the demo, it seems relatively easy to build a filter to remove adversarial suffix before feeding the query into LLM…
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Perplexity Labs Launches Web App for LLaMa 2
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Perplexity Labs https://
bit.ly/3K7P5RI
Web app for LLaMa 2!
#AI #MachineLearning #DeepLearning #LLMs #DataScience -
Choosing the Right Llama 2 Model Variant for Your Needs
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There are multiple variant Llama 2 models on Replicate (7B, 13B, 70B, chat vs base, etc), each with their own strengths. Check out the post to see which one is right for your needs. https://
replicate.com/blog/run-llama
-2-with-an-api#choosing-which-model-to-use
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Llama 2: First Open-Source Model Matching OpenAI’s Caliber
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Llama 2 is the first open-source language model of the same caliber as OpenAI's models. You can run it on Replicate using JavaScript, Python, cURL, Go, Swift, or any other language. Here's a guide to get you started running Llama 2 with an API.