Papers

[Paper Reading] Kangaroo: Lossless Self-Speculative Decoding via Double Early Exiting

Clay
2024-06-032024-07-25
Machine Learning, Python

Introduction

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.

Clay
2024-01-222024-07-25
Machine Learning

Introduction

RAG-based LLM is a well-known architecture in current usage of Large Language Models (LLM). It involves “retrieval” to provide the model with prior knowledge that it lacks during training, enabling the model to answer questions in the context of specific information.

Clay
2024-01-212024-07-25
Machine Learning

Introduction

The wave of large models has been unstoppable since the release of ChatGPT in November 2022. Up to now, the scale of open-source Large Language Models (LLMs) continues to increase, such as LLaMA-2-70B and Falcon-180B, to name a few.

Clay
2024-01-182024-07-25
Machine Learning

Introduction

Paper link: https://arxiv.org/abs/2212.13345

The author of this research work is the renowned figure in the field of deep learning, Geoffrey Hinton, who was originally a researcher at Google Brain when he initially wrote this paper (he left in 2023).

Clay
2023-06-052024-07-25
Machine Learning, PyTorch

Introduction

Meta AI has indeed been incredibly powerful recently, seemingly securing its position as a giant in AI research and development in no time at all, and what’s more, it sets the bar high with all its top-tier open-source contributions. From Segment Anything that can segment objects in the image domain, to the public large language model and foundational model, LLaMA (yes, the one causing the llama family appear!), to the recent ImageBind that can transform six modalities and the Massively Multilingual Speech (MMS) project… I must say, for an ordinary person like me, it’s quite an effort to keep up with how to use these technologies, let alone trying to chase their technical prowess.

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Papers

[Paper Reading] Kangaroo: Lossless Self-Speculative Decoding via Double Early Exiting

Introduction

[Paper Reading] Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection

Introduction

[Paper Reading] QLoRA: Efficient Finetuning of Quantized LLMs

Introduction

[Paper Reading] The Forward-Forward Algorithm: Some Preliminary Investigation

Introduction

ImageBind: A Experience Notes on a Multimodal Vector Transformation Model

Introduction