SiLU (Sigmoid Linear Unit) activation function is similar to Swish function, Swish just have additional trainable beta parameter. Many large language model (LLM) also adopt this approach, primarily in some exploratory models that use activation functions other than ReLU, such as the classic Llama architecture.
Read More »[Machine Learning] Note Of SiLU Activation Function
For several months, I have benefited greatly from the Unsloth project, primarily because a significant part of my job involves fine-tuning large language models (LLMs). Fine-tuning LLMs is extremely time-consuming; aside from data collection, the biggest time sink is the endless GPU-powered fine-tuning process.
Read More »Note Of Unsloth Accelerate Fine-tuning Open Source Project
The accelerated framework is proposed by Huawei Noah’s Ark Lab, it replaces the small model used in the original speculative decoding with the shallow sub-network of the large model. Additionally, it employs an extra-trained adapter and the model’s own decoding head to generate speculative tokens, which are then verified by the large model. The subsequent operations are quite similar to the original speculative decoding process.
Read More »[Paper Reading] Kangaroo: Lossless Self-Speculative Decoding via Double Early Exiting
RESTful design (Representational State Transfer, REST) is an architectural style for designing network applications. It follows principles that make network applications simpler, more scalable, and easier to maintain.
Read More »Note Of RESTful (With Python FastAPI + CURL Example)
When assigning identifiers to our data, if we want each data to have a unique identifier rather than a simple sequential number, UUID is the most common method we used.
So, what is UUID?
Read More »Note Of Universally Unique Identifier (UUID)
