Topic: model-distillation Goto Github
Some thing interesting about model-distillation
Some thing interesting about model-distillation
model-distillation,Images to inference with no labeling (use foundation models to train supervised models).
Organization: autodistill
Home Page: https://docs.autodistill.com
model-distillation,Autodistill Google Cloud Vision module for use in training a custom, fine-tuned model.
Organization: autodistill
Home Page: https://docs.autodistill.com
model-distillation,Use AWS Rekognition to train custom models that you own.
Organization: autodistill
Home Page: https://docs.autodistill.com
model-distillation,Our open source implementation of MiniLMv2 (https://aclanthology.org/2021.findings-acl.188)
Organization: bloomberg
model-distillation,Use LLaMA to label data for use in training a fine-tuned LLM.
User: capjamesg
model-distillation,Awesome Deep Model Compression
User: chadhgy
model-distillation,A framework for knowledge distillation using TensorRT inference on teacher network
User: dataplayer12
model-distillation,Awesome Knowledge Distillation
User: dkozlov
model-distillation,Model distillation of CNNs for classification of Seafood Images in PyTorch
User: dogeplusplus
model-distillation,The Codebase for Causal Distillation for Language Models (NAACL '22)
User: frankaging
model-distillation,The Codebase for Causal Distillation for Task-Specific Models
User: frankaging
Home Page: https://arxiv.org/abs/2112.02505
model-distillation,π PyTorch Implementation of "Progressive Distillation for Fast Sampling of Diffusion Models(v-diffusion)"
User: hramchenko
model-distillation,Repository for the publication "AutoGraph: Predicting Lane Graphs from Traffic"
User: jzuern
Home Page: http://autograph.cs.uni-freiburg.de/
model-distillation,Matching Guided Distillation (ECCV 2020)
User: kaiyuyue
Home Page: https://kaiyuyue.com/mgd
model-distillation,[Master Thesis] Research project at the Data Analytics Lab in collaboration with Daedalean AI. The thesis was submitted to both ETH ZΓΌrich and Imperial College London.
User: konstantinosbarmpas
model-distillation,Mechanistically interpretable neurosymbolic AI (Nature Comput Sci 2024): losslessly compressing NNs to computer code and discovering new algorithms which generalize out-of-distribution and outperform human-designed algorithms
User: pauljblazek
Home Page: https://rdcu.be/dy2Go
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