Scaling up BERT-like model Inference on modern CPU - Part 2
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Michael Benayoun
michaelbenayoun
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Papers and resources related to distributed training.
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PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel
Paper • 2304.11277 • Published • 1 -
Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism
Paper • 1909.08053 • Published • 2 -
Reducing Activation Recomputation in Large Transformer Models
Paper • 2205.05198 • Published -
GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism
Paper • 1811.06965 • Published
models
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michaelbenayoun/llama-2-tiny-4kv-heads-4layers-random
Text Generation
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2.04k
michaelbenayoun/t5-tiny-random
Text2Text Generation
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58
michaelbenayoun/llama-2-tiny-4kv-heads-2layers-random
Feature Extraction
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748
michaelbenayoun/llama-2-tiny-4kv-heads-8layers-random
Feature Extraction
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4
michaelbenayoun/llama-2-tiny-4kv-heads-16layers-random
Feature Extraction
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1.04k
michaelbenayoun/llama-2-tiny-16layers-random
Feature Extraction
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1.04k
michaelbenayoun/llama-2-tiny-16layers-32kv-heads-random
Feature Extraction
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michaelbenayoun/gpt-neox-tiny-4layers-random
Feature Extraction
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michaelbenayoun/mistral-tiny-4layers-8kv-heads-random
Text Generation
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597
michaelbenayoun/llama-2-tiny-4layers-random
Text Generation
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50
datasets
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