Understanding Transformers Through Llama Model Architecture

Understanding Transformers Through Llama Model Architecture

Understanding Transformers Through Llama Model Architecture Llama Nuts and Bolts is an open-source project on GitHub that rewrites the inference process of the Llama 3.1 8B-Instruct model (80 billion parameters) from scratch using the Go language. The author is Adil Alper DALKIRAN from Turkey. If you are interested in how LLMs (Large Language Models) and … Read more

Google Proposes New Titans Architecture Beyond Transformers

Google Proposes New Titans Architecture Beyond Transformers

-Titans: Learning to Memorize at Test Time Ali Behrouz† , Peilin Zhong† , and Vahab Mirrokni† Google Research Abstract For more than a decade, extensive research has been conducted on how to effectively utilize recurrent models and attention mechanisms.While recurrent models aim to compress data into fixed-size memories (known as hidden states), attention allows for … Read more

BERT Paper Notes

BERT Paper Notes

Author: Prince Changqin (NLP Algorithm Engineer) Bert, Pre-training of Deep Bidirectional Transformers for Language Understanding Note Paper: https://arxiv.org/pdf/1810.04805.pdf Code: https://github.com/google-research/bert The core idea of Bert: MaskLM utilizes bidirectional context + MultiTask. Abstract BERT obtains a deep bidirectional representation of text by jointly training the context across all layers. Introduction Two methods to apply pre-trained models … Read more

BERT Implementation in PyTorch: A Comprehensive Guide

BERT Implementation in PyTorch: A Comprehensive Guide

Selected from GitHub Author: Junseong Kim Translated by Machine Heart Contributors: Lu Xue, Zhang Qian Recently, Google AI published an NLP paper introducing a new language representation model, BERT, which is considered the strongest pre-trained NLP model, setting new state-of-the-art performance records on 11 NLP tasks. Today, Machine Heart discovered a PyTorch implementation of BERT … Read more

Qwen 1.5 Open Source! Best Practices for Magic Adaptation!

Qwen 1.5 Open Source! Best Practices for Magic Adaptation!

In recent months, the Tongyi Qianwen team has been working hard to explore how to build a ‘good’ model while optimizing the developer experience. Just before the Chinese New Year, the Tongyi Qianwen team shared the next version of the Qwen open-source series, Qwen 1.5. Qwen 1.5 has open-sourced six sizes of foundational and chat … Read more

A Powerful Python Library: Call GPT-4 with One Line of Code!

A Powerful Python Library: Call GPT-4 with One Line of Code!

Hello everyone! Today I want to reveal an AI gem in the Python world——Hugging Face’s transformers library! This library is like having a legion of AI assistants, specifically designed to call various top AI models. Using transformers is simply the Swiss Army knife of AI development! Come on, let’s explore the magical charm of the … Read more

Cohere’s Open Source 35B Model Surpasses Mixtral in RAG and Tool Capabilities

Cohere's Open Source 35B Model Surpasses Mixtral in RAG and Tool Capabilities

https://txt.cohere.com/command-r/ https://huggingface.co/CohereForAI/c4ai-command-r-v01 1. RAG Performance On multiple datasets, it far exceeds the Mixtral MoE model. By using their own embeddings and reranking, it significantly outperforms open-source models. 2. Tool Capabilities The tool capabilities are slightly better than Mixtral and significantly outperform GPT-3.5. 3. Multilingual Capabilities Supports English, French, Spanish, Italian, German, Brazilian Portuguese, Japanese, Korean, … Read more

Introduction to Transformers in NLP

Introduction to Transformers in NLP

Recently, Hugging Face has a very popular book titled “nlp-with-transformers”, and we will be updating practical tutorials related to transformers, so let’s get hands-on learning! Original text: https://www.oreilly.com/library/view/natural-language-processing/9781098103231/ch01.html Warning ahead, there will be a strong flavor of translation, so please enjoy while it’s fresh. Hello Transformers In 2017, researchers at Google published a paper proposing … Read more

High-Speed Download of HuggingFace Models in China

High-Speed Download of HuggingFace Models in China

Author: Apathy Link: https://zhuanlan.zhihu.com/p/669120427 Note: This article has been tested and is effective, highly recommended. Users in China can use the official HuggingFace download tool huggingface-cli and hf_transfer to download models and datasets from the HuggingFace mirror site at high speed. HuggingFace-Download-Acceleratorgithub.com/LetheSec/HuggingFace-Download-Accelerator Quick Start 1. Clone the project to your local machine: git clone https://github.com/LetheSec/HuggingFace-Download-Accelerator.git … Read more

Unlocking the Magic of Natural Language Processing with HuggingFace Transformers

Unlocking the Magic of Natural Language Processing with HuggingFace Transformers

Embark on a Journey of Natural Language Magic with Python and HuggingFace Transformers, Unlocking Infinite Text Possibilities Hey there, Python newbies and enthusiasts! Today, we are going to explore a super powerful Python library in the field of natural language processing — HuggingFace Transformers. It’s like a treasure chest full of magical tools that helps … Read more