GitHub topics: large-scale-deployment
ksm26/Efficiently-Serving-LLMs
Learn the ins and outs of efficiently serving Large Language Models (LLMs). Dive into optimization techniques, including KV caching and Low Rank Adapters (LoRA), and gain hands-on experience with Predibase’s LoRAX framework inference server.
Language: Jupyter Notebook - Size: 2.34 MB - Last synced at: 3 days ago - Pushed at: about 1 year ago - Stars: 15 - Forks: 4
Related Keywords
batch-processing
1
deep-learning-techniques
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inference-optimization
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large-scale-deployment
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machine-learning-operations
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model-acceleration
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model-inference-service
1
model-serving
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optimization-techniques
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performance-enhancement
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scalability-strategies
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server-optimization
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serving-infrastructure
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text-generation
1