6/ They are only getting better! LoRA fine-tuning with Predibase makes inference 3x faster compared to the base model.
LLMS
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How LoRA is Transforming LLM Fine-tuning Techniques
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1/ Curious how #LoRA is changing fine-tuning? Read our latest blog post to learn more! #llm #finetune
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LoRA Achieves Comparable Performance to Full Fine-Tuning
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2/ No trade-off in performance. A 2021 study demonstrated comparable performance between LoRA and full fine-tuning.
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LoRA Training Parameters: Minimal Memory Footprint at 0.2%
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3/ Extremely low memory footprint. LoRA trainable parameters are only 0.2% of total amount of model parameters.
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Running LM Studio on MacBook M1 Pro with 16GB RAM
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I am running this on Macbook M1 pro (16GB RAM) using the @LMStudioAI
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Running LM Studio on MacBook M1 Pro: Hardware Requirements
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I am running this on Macbook M1 pro (16GB RAM) using the @LMStudioAI
. And ofc, you need some hardware to start with. Nothing will be free free lol -
Running LM Studio on MacBook M1 Pro with 16GB RAM
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I am running this on Macbook M1 pro (16GB RAM) using the @LMStudioAI
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Function Calling Leaderboards and Model Capabilities Overview
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its a moving target so better to just know some of the leaderboards. look up function calling leaderboards. i think gorilla may have one but idk if up to date. llama3 wouldnt have it directly but some finetunes would. would also check out cohere command r
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Grok AI adds Socrates mode and teases image generation features
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Read more https://
testingcatalog.com/icymi-grok-int
rospects-with-socrates-mode-and-teases-image-generation-and-web-search-features/
…