New course with Hugging Face: Quantization in Depth 🤗
Enroll now: https://bit.ly/44nXDNa
We’re excited to introduce Quantization in Depth, a new short course built in collaboration with Hugging Face, taught by Younes Belkada and Mark Sun, and designed to provide a deep technical understanding of quantization.
This course lets you build and customize your own linear quantizer from scratch, going beyond standard open source libraries such as PyTorch and Quanto, which were the focus of our previous course, Quantization Fundamentals.
Join in to:
- Implement and customize linear quantization from scratch, trading off between space and performance, and choosing between two "modes:" asymmetric and symmetric; and three granularities: per-tensor, per-channel, and per-group quantization.
- Measure the quantization error of each of these options as you balance the performance and space tradeoffs for each option.
- Build your own quantizer in PyTorch, to quantize any open source model's dense layers from 32 bits to 8 bits.
- Go beyond 8 bits, and pack four 2-bit weights into one 8-bit integer, and also, learn to unpack them.
Quantization in Depth gives you the foundation to study more advanced quantization methods, some of which are recommended at the end of the course.
Learn more: https://bit.ly/44nXDNa
Видео New course with Hugging Face: Quantization in Depth 🤗 канала DeepLearningAI
We’re excited to introduce Quantization in Depth, a new short course built in collaboration with Hugging Face, taught by Younes Belkada and Mark Sun, and designed to provide a deep technical understanding of quantization.
This course lets you build and customize your own linear quantizer from scratch, going beyond standard open source libraries such as PyTorch and Quanto, which were the focus of our previous course, Quantization Fundamentals.
Join in to:
- Implement and customize linear quantization from scratch, trading off between space and performance, and choosing between two "modes:" asymmetric and symmetric; and three granularities: per-tensor, per-channel, and per-group quantization.
- Measure the quantization error of each of these options as you balance the performance and space tradeoffs for each option.
- Build your own quantizer in PyTorch, to quantize any open source model's dense layers from 32 bits to 8 bits.
- Go beyond 8 bits, and pack four 2-bit weights into one 8-bit integer, and also, learn to unpack them.
Quantization in Depth gives you the foundation to study more advanced quantization methods, some of which are recommended at the end of the course.
Learn more: https://bit.ly/44nXDNa
Видео New course with Hugging Face: Quantization in Depth 🤗 канала DeepLearningAI
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
DeepLearning.AI NLP Learner Community Event ft. Mo Rebaie#2 Machine Learning Engineering for Production (MLOps) Specialization [Course 1, Week 1, Lesson 2]#9 Machine Learning Engineering for Production (MLOps) Specialization [Course 1, Week 2, Lesson 1]#26 AI for Good Specialization [Course 1, Week 2, Lesson 2]#29 Machine Learning Engineering for Production (MLOps) Specialization [Course 1, Week 3, Lesson 5]#28 Machine Learning Specialization [Course 1, Week 2, Lesson 2]#30 Machine Learning Specialization [Course 1, Week 2, Lesson 2]#27 Machine Learning Engineering for Production (MLOps) Specialization [Course 1, Week 3, Lesson 3]Addressing Data Mismatch (C3W2L06)Augmenting Data (TensorFlow in Practice)#BeADeepLearner like Matt Struble with DeepLearning.AI#5 AI for Good Specialization [Course 1, Week 1, Lesson 2]#26 Machine Learning Specialization [Course 1, Week 2, Lesson 2]#18 Machine Learning Engineering for Production (MLOps) Specialization [Course 1, Week 2, Lesson 10]#12 Machine Learning Engineering for Production (MLOps) Specialization [Course 1, Week 2, Lesson 4]#25 Machine Learning Engineering for Production (MLOps) Specialization [Course 1, Week 3, Lesson 1]deeplearning.ai Learner Community Event ft. Roger Smith#22 Machine Learning Engineering for Production (MLOps) Specialization [Course 1, Week 2, Lesson 14]#28 Machine Learning Engineering for Production (MLOps) Specialization [Course 1, Week 3, Lesson 4]#BeADeepLearner like Yudhiesh Ravindran with DeepLearning.AI