nlp

7 Day AI ML Fundamentals Workshop The purpose of this FREE workshop is 1. To give you a boost of getting started with AI. 2. A life-long community with a similar mindset. 3. strong grip on fundamentals that the advanced concepts will be easy to understand.

Turn speech into semantic paragraphs in real time, on a CPU (no GPU) — single-pass streaming chunker + Moonshine STT + a live mic demo. Plus a transcribe/chunk/summarize API.

Source code for our EMNLP'21 paper 《Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuning》

State-of-the-art prompting techniques implementation with DSpy - Manager-style prompts, role personas, meta-prompting, and more

Build Semantic Search with S-BERT and Fine-tune your model in unsupervised way

TrAVis: Visualise BERT attention in your browser

Search Git commits in natural language

B站视频分析助手：提取字幕/评论/关键帧并生成深度分析报告。

Lightweight multilingual language models for consumer hardware

Annotation meets Large Language Models (ChatGPT, GPT-3 and alike).

🤖📇 handling multiple nlp task in one pipeline

SynthGenAI - Package for Generating Synthetic Datasets using LLMs.

Tokenizer POS-Tagger and Dependency-parser with BERT/RoBERTa/DeBERTa/GPT models for Japanese and other languages

Model zoo for different kinds of uncertainty quantification methods used in Natural Language Processing, implemented in PyTorch.

Python temellerinden Reinforcement Learning'e kadar uzanan, 22 modüllük uçtan uca Veri Bilimi & Makine Öğrenmesi yol haritası. Her konuda çalıştırılmış notebook'lar ve PDF tekrar soruları.

13 projects using ChatGPT API, Whisper, Embeddings, and DALL-E with Python.

3DCF / doc2dataset: token-efficient document layer with NumGuard numeric integrity and multi-framework exports for RAG & fine-tuning.

A repository containing comprehensive Neural Networks based PyTorch implementations for the semantic text similarity task, including architectures such as: Siamese LSTM Siamese BiLSTM with Attention Siamese Transformer Siamese BERT.

A targeted resource for mastering LangChain, featuring practice problems, code examples, and interview-focused concepts for building AI applications with Python. Covers chaining LLMs, memory management, and tool integration for technical interview success.

The FunctionChain is a tool that simplifies and organizes the process of invoking OpenAI functions in your Node.js applications. With this toolkit, you can easily scaffold out and isolate all the OpenAI function calls you need, making your code more modular, maintainable, and scalable.