Source: Deephub Imba This article is about 1500 words long and takes about 5 minutes to read. In this article, we want to demonstrate how to use the pre-trained weights of an encoder-only model to provide a good starting point for our fine-tuning. BERT is a famous and powerful pre-trained encoder model. Let’s see how … Read more
This article is also published on my personal website, where the formula images display better. Welcome to visit: https://lulaoshi.info/machine-learning/attention/bert Since the emergence of BERT (Bidirectional Encoder Representations from Transformer) [1], a new paradigm has opened up in the field of NLP. This article mainly introduces the principles of BERT and how to use the transformers … Read more
MLNLP community is a well-known machine learning and natural language processing community both domestically and internationally, covering NLP master’s and doctoral students, university professors, and corporate researchers. The vision of the community is to promote communication and progress between the academic and industrial sectors of natural language processing and machine learning, as well as enthusiasts, … Read more
MLNLP community is a well-known machine learning and natural language processing community, covering domestic and international NLP master’s and doctoral students, university teachers, and corporate researchers. Community Vision is to promote communication and progress between the academic and industrial sectors of natural language processing and machine learning, especially for the progress of beginners. Reprinted from … Read more
Source: DeepHub IMBA This article is approximately 2300 words long and is recommended for a 10-minute read. This article introduces how to run LLM on high-performance CPU using the llama.cpp library in Python. Large Language Models (LLM) Are Becoming Increasingly Popular, But They Require A Lot Of Resources, Especially GPU. Large language models (LLM) are … Read more
https://www.itdog.cn/http/ If you cannot directly download models from HuggingFace[1], you can use the https://github.com/AlphaHinex/hf-models repository and build a Docker image using GitHub Actions[2]. In the image, use huggingface_hub[3] to download the required models, then push the image to Docker Hub[4]. Finally, you can download the model using the image. 1Available Models (tags) Currently available models … Read more
Users of ComfyUI know that it is necessary to frequently download various large models from Huggingface, and during the download, three major problems need to be solved: 1. Network issues; domestic users cannot directly access and download large models. 2. Large file download issues; due to unstable networks or unstable proxies, downloads of large files … Read more
Every time I start a new machine learning project, the first thing that gives me a headache is not model selection, but the dataset. Downloading datasets, unzipping, cleaning, formatting—a series of steps makes me feel like I’m facing a “programmer’s physical labor” challenge. And once the dataset is too large to load into memory all … Read more
Downloading Assuming we need to download the <span><span>Qwen2.5-0.5B-Instruct</span></span> model from Huggingface. 1. Using git lfs Git LFS is an extension developed by GitHub to support large files in Git. Installation on Mac: brew install git-lfs Installation on Linux: curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | sudo bash sudo apt install git-lfs git lfs install Download the large model: … Read more
Produced by Big Data Digest After the explosive popularity of ChatGPT, the AI community has entered a “hundred model battle.” Recently, Nathan Lambert, a machine learning scientist at Huggingface, organized the current strengths of large models from an open-source perspective in a blog post, offering many profound insights. What this looks like is instead of … Read more