https://github.com/pwc-1/Paper-10/tree/main/tinybert
TinyBERT: Distilling BERT for Natural Language Understanding
Papers with Code 아카이브
Knowledge Distillation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Knowledge distillation is the process of transferring knowledge from a large model to a smaller one. While large models (such as very deep neural networks or ensembles of many models) have higher knowledge capacity than small models, this capacity might not be fully utilized.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/pwc-1/Paper-8/tree/main/clip
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/pwc-1/Paper-8/tree/main/dbrx
https://github.com/pwc-1/Paper-9/tree/main/1/tinybert
TinyBERT: Distilling BERT for Natural Language Understanding
https://github.com/pwc-1/Paper-9/tree/main/graphormer
Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets
https://github.com/pytorch/rl
https://github.com/pytorch/vision
https://github.com/qampspring2023/qgpt-issue-31
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
https://github.com/qdezkaggle/DetectionTool
https://github.com/qianfu1997/synchro_new
https://github.com/qingyujean/Classification-on-imbalanced-data
https://github.com/qingzwang/DiversityMetrics
https://github.com/qizekun/ReCon
https://github.com/qizekun/vpp
https://github.com/qtli/gsm-plus
AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agents
https://github.com/qub-blesson/ScissionTL
Scission: Performance-driven and Context-aware Cloud-Edge Distribution of Deep Neural Networks
https://github.com/qw61116111/ECG
https://github.com/qxb-tyust/location
https://github.com/qywu/PRAL
A Tailored Pre-Training Model for Task-Oriented Dialog Generation
https://github.com/rahowa/catboost_focal_loss
https://github.com/rahulvigneswaran/Class-Balanced-Distillation-for-Long-Tailed-Visual-Recognition.pytorch
Class-Balanced Distillation for Long-Tailed Visual Recognition
https://github.com/rainofmine/Face_Attention_Network
https://github.com/rajathik/ObjectDetection
https://github.com/ramanakshay/clip
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/raminaghods/FuseInit
https://github.com/raspstephan/sugar-flower-fish-or-gravel
https://github.com/rebeccagio/object_detection
https://github.com/reczoo/FuxiCTR
BARS-CTR: Open Benchmarking for Click-Through Rate Prediction
https://github.com/reczoo/recsys2024_ctr_challenge
BARS-CTR: Open Benchmarking for Click-Through Rate Prediction
https://github.com/redcaps-dataset/redcaps-downloader
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/rejuvyesh/rllab
Benchmarking Deep Reinforcement Learning for Continuous Control
https://github.com/renzelou/pick-rank
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks
https://github.com/reycn/multi-modal-scale
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
https://github.com/ricardordb/bert
Well-Read Students Learn Better: On the Importance of Pre-training Compact Models
https://github.com/richardrl/cartpole-request-for-research
Benchmarking Deep Reinforcement Learning for Continuous Control
https://github.com/ringbdstack/socialed
Transferring Knowledge Distillation for Multilingual Social Event Detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.