Machine Learning

Qwen3-TTS Family is Now Open Sourced: Voice Design, Clone, and Generation!

qwenlm.github.io

GithubHuggingFaceHuggingface DemoModelScope DemoPaper Qwen3-TTS is a series of powerful speech generation capabilities developed by Qwen, offering comprehensive support for voice clone, voice design, ultra-high-quality human-like speech generation, and natural language-based voice control. It…

5 weeks ago

Fine-tuning with gpt-oss and Hugging Face Transformers | OpenAI Cookbook

cookbook.openai.com

Authored by: Edward Beeching, Quentin Gallouédec, and Lewis Tunstall Large reasoning models like OpenAI o3 generate a chain-of-thought to improve the accuracy and quality of their responses. However, most of these models reason in English, even when a question is asked in another language. In this…

Aug 13, 2025

PostgreSQL as a Vector Database: A Pgvector Tutorial

tigerdata.com

Vector databases enable efficient storage and searching of vector data. They are essential for developing and maintaining AI applications using large language models (LLMs). With some help from the pgvector extension, you can leverage PostgreSQL as a vector database to store and query OpenAI…

Jul 28, 2025

Elasticsearch kNN Query: An expert way to do kNN search - Elasticsearch Labs

elastic.co

kNN search as a top-level section kNN search in Elasticsearch is organized as a top level section of a search request. We have designed it this way so that: It can always return global k nearest neighbors regardless of a number of shardsThese global k results are combined with a results from other…

Jul 28, 2025

Vector Search in OpenSearch vs. Elasticsearch: A Comparison

opster.com

By Opster Expert Team - Valentin Crettaz Updated: Feb 22, 2024 | 6 min read Quick links Overview In a previous series of articles, we delved deep into the vast topic of semantic search and how that was designed and implemented in both OpenSearch and Elasticsearch. The second and third articles…

Jul 28, 2025

pytorch-labs/gpt-fast: Simple and efficient pytorch-native transformer text generation in <1000 LOC of python.

github.com

gpt-fast Simple and efficient pytorch-native transformer text generation. Featuring: Very low latency <1000 lines of python No dependencies other than PyTorch and sentencepiece int8/int4 quantization Speculative decoding Tensor parallelism Supports Nvidia and AMD GPUs This is NOT intended to be a…

Mar 5, 2025

GitHub - unslothai/unsloth: Finetune Llama 3.3, DeepSeek-R1 & Reasoning LLMs 2x faster with 70% less memory

github.com

Train gpt-oss, DeepSeek, Gemma, Qwen & Llama 2x faster with 70% less VRAM! ✨ Train for Free Notebooks are beginner friendly. Read our guide. Add dataset, run, then deploy your trained model. Model Free Notebooks Performance Memory use Qwen3.5 (4B) ▶️ Start for free 1.5x faster 60% less gpt-oss (20B)…

Feb 11, 2025

Classifying articles via URLs

attentionmarkets.substack.com

Today, I want to work through a small exercise in language modeling. A common NLP task for researchers working with news articles is some form of topic modeling. By getting a sense of what news stories are about, aggregated into a defined vocabulary of labels, researchers can make comparisons across…

Feb 3, 2025

Text Classification using Custom Data and PyTorch

medium.com

sandeep pandey 5 min read· May 17, 2023 -- Press enter or click to view image in full size Photo by Max Chen on Unsplash Text classification is a fundamental natural language processing (NLP) task that involves assigning predefined categories or labels to text documents. PyTorch, a popular deep…

Jan 29, 2025

Develop Your First Neural Network with PyTorch, Step by Step - MachineLearningMastery.com

machinelearningmastery.com

PyTorch is a powerful Python library for building deep learning models. It provides everything you need to define and train a neural network and use it for inference. You don’t need to write much code to complete all this. In this pose, you will discover how to create your first deep learning neural…

Jan 28, 2025

wordfreq/SUNSET.md at master · rspeer/wordfreq

github.com

Note from September 2024 This documentation page has gotten a lot of attention recently! I think most of the people who find it understand where I'm coming from. I'd like to highlight a couple of things, now that people are linking to this page from all sorts of contexts. I still work on open-source…

Oct 3, 2024

seekbytes/IPA: GUI analyzer for deep-diving into PDF files. Detect malicious payloads, understand object relationships, and extract key information for threat analysis.

github.com

Interactive PDF Analysis Interactive PDF Analysis (also called IPA) allows any researcher to explore the inner details of any PDF file. PDF files may be used to carry malicious payloads that exploit vulnerabilities, and issues of PDF viewer, or may be used in phishing campaigns as social engineering…

Sep 6, 2024

Run the strongest open-source LLM model: Llama3 70B with just a single 4GB GPU!

ai.gopubby.com

Gavin Li 4 min read· Apr 21, 2024 -- Press enter or click to view image in full size The strongest open source LLM model Llama3 has been released, some followers have asked if AirLLM can support running Llama3 70B locally with 4GB of VRAM. The answer is YES. Here we go. Moreover, how does Llama3’s…

May 31, 2024

Reproducing GPT-2 (124M) in llm.c in 90 minutes for $20 · karpathy/llm.c · Discussion #481

github.com

Replies: 48 comments · 83 replies Oldest Newest Top Comment options Uh oh! There was an error while loading. . {{title}} Something went wrong. Uh oh! There was an error while loading. . timlmit - boss <3 Beta Was this translation helpful? You must be logged in to vote All reactions ❤️ 8 0 replies…

May 29, 2024

Techniques for automatic summarization of documents using language models | Amazon Web Services

aws.amazon.com

Summarization is the technique of condensing sizable information into a compact and meaningful form, and stands as a cornerstone of efficient communication in our information-rich age. In a world full of data, summarizing long texts into brief summaries saves time and helps make informed decisions.…

Mar 1, 2024

How to parallelize python api calls?

stackoverflow.com

Home Questions AI Assist Tags Challenges Chat Articles Users Jobs Companies Communities for your favorite technologies. Explore all Collectives Stack Internal Stack Overflow for Teams is now called Stack Internal. Bring the best of human thought and AI automation together at your work. Try for free…

Jan 10, 2024

Making 1 million requests with python-aiohttp

pawelmhm.github.io

In this post I’d like to test limits of python aiohttp and check its performance in terms of requests per minute. Everyone knows that asynchronous code performs better when applied to network operations, but it’s still interesting to check this assumption and understand how exactly it is better and…

Jan 10, 2024

Notes on Abstractive Summarization: PegasusXSUM and T5

medium.com

Press enter or click to view image in full size ‘Cloud observer’ VR art created by iva vrtaric Iva Vrtaric @ Tesla Institute 9 min read· May 14, 2022 -- Recently, it has become increasingly common to pre-train the entire model on a data-rich task. Ideally, this pre-training causes the model to…

Jan 8, 2024

Build an Automatic Abstractive Text Summarizer in Ten minutes

medium.com

using Transformers, Torch, SentencePiece libraries in Python. Dhiraj Prakash 4 min read· Sep 21, 2021 -- Press enter or click to view image in full size Photo by Mel Poole on Unsplash Text Summarization is the process of shortening long text into shorter text while retaining the key elements and…

Jan 8, 2024

Text Summarization in Python using Extractive method (including end-to-end implementation)

medium.com

What is Text Summarization Text summarization is a process of creating concise version of the original text while retaining key information. Humans are naturally good summarizers for we have the ability to understand the overall meaning of a text just by reading it. But how can machines do the same…

Jan 8, 2024

Recommendation using embeddings and nearest neighbor search | OpenAI Cookbook

cookbook.openai.com

Recommendations are widespread across the web. ‘Bought that item? Try these similar items.’ ‘Enjoy that book? Try these similar titles.’ ‘Not the help page you were looking for? Try these similar pages.’ This notebook demonstrates how to use embeddings to find similar items to recommend. In…

Jan 8, 2024