Natural language processing (NLP) is a field of computer science that studies how computers and humans interact. In the 1950s, Alan Turing published an article that proposed a measure of intelligence, now called the Turing test. More modern techniques, such as deep learning, have produced results in the fields of language modeling, parsing, and natural-language tasks.
"Excited to share my latest project on LinkedIn! 🎥 Presenting my movie recommendation system deployed on Streamlit. With the power of NLP and machine learning, it suggests 5 similar movies based on your search query, drawing from a dataset of 5000 Hollywood movies. Discover your next favorite flick effortlessly! 🍿💡 #MovieRecommendation #NLP #ML
An even simpler way to generate text with LLMs.
Large Language Model Text Generation Inference
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Finite state and Constraint Grammar based analysers and proofing tools, and language resources for the Kalaallisut (Greenlandic) language
A PyTorch implementation of the original Transformer.
A Framework of Small-scale Large Multimodal Models
QuillGPT is an implementation of the GPT decoder block based on the architecture from Attention is All You Need paper by Vaswani et. al. in PyTorch. Additionally, this repository contains two pre-trained models — Shakespearean GPT and Harpoon GPT, a Streamlit Playground, Containerized FastAPI Microservice, training - inference scripts & notebooks.
Easy-to-use and high-performance NLP and LLM framework based on MindSpore, compatible with models and datasets of 🤗Huggingface.
Argilla is a collaboration platform for AI engineers and domain experts that require high-quality outputs, full data ownership, and overall efficiency.
RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.
Summarize text or PDF file using ChatGPT
Conversational AI Platform to build effective Proactive Digital Assistants using Visual LLM Chaining
Open source libraries and APIs to build custom preprocessing pipelines for labeling, training, or production machine learning pipelines.
A one-stop data processing system to make data higher-quality, juicier, and more digestible for LLMs! 🍎 🍋 🌽 ➡️ ➡️🍸 🍹 🍷为大语言模型提供更高质量、更丰富、更易”消化“的数据！
Machine Learning Toolbox 2
🦉 Snow Owl Terminology Server - production-ready, scalable, supports FHIR R4, FHIR R5, SNOMED CT International and Extensions, LOINC, ICD-10, dm+d, custom code systems and many others
Created by Alan Turing