Search Results for "nlp"
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Showing 17 open source projects for "nlp"
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spacy-llm
Integrating LLMs into structured NLP pipelines
Large Language Models (LLMs) feature powerful natural language understanding capabilities. With only a few (and sometimes no) examples, an LLM can be prompted to perform custom NLP tasks such as text categorization, named entity recognition, coreference resolution, information extraction and more. This package integrates Large Language Models (LLMs) into spaCy, featuring a modular system for fast prototyping and prompting, and turning unstructured responses into robust outputs for various NLP tasks, no training data required. -
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STORM
An LLM-powered knowledge curation system that researches topics
STORM is an open-source virtual assistant framework developed by Stanford's OVAL lab. It is designed for creating natural language interfaces and assistants that can interact with APIs, databases, and services in a modular way. -
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NVIDIA NeMo
Toolkit for conversational AI
NVIDIA NeMo, part of the NVIDIA AI platform, is a toolkit for building new state-of-the-art conversational AI models. NeMo has separate collections for Automatic Speech Recognition (ASR), Natural Language Processing (NLP), and Text-to-Speech (TTS) models. Each collection consists of prebuilt modules that include everything needed to train on your data. Every module can easily be customized, extended, and composed to create new conversational AI model architectures. Conversational AI architectures are typically large and require a lot of data and compute for training. ... -
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llama.cpp Python Bindings
Python bindings for llama.cpp
llama-cpp-python provides Python bindings for llama.cpp, enabling the integration of LLaMA (Large Language Model Meta AI) language models into Python applications. This facilitates the use of LLaMA's capabilities in natural language processing tasks within Python environments. -
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BertViz
BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)
BertViz is an interactive tool for visualizing attention in Transformer language models such as BERT, GPT2, or T5. It can be run inside a Jupyter or Colab notebook through a simple Python API that supports most Huggingface models. BertViz extends the Tensor2Tensor visualization tool by Llion Jones, providing multiple views that each offer a unique lens into the attention mechanism. The head view visualizes attention for one or more attention heads in the same layer. It is based on the... -
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llms-from-scratch-cn
Build a large language model from 0 only with Python foundation
llms-from-scratch-cn is an educational open-source project designed to teach developers how to build large language models step by step using practical code and conceptual explanations. The repository provides a hands-on learning path that begins with the fundamentals of natural language processing and gradually progresses toward implementing full GPT-style architectures from the ground up. Rather than focusing on using pre-trained models through APIs, the project emphasizes understanding... -
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TigerBot
TigerBot: A multi-language multi-task LLM
TigerBot is an open-source family of large language models designed to support multilingual and multi-task natural language processing applications. The project focuses on building high-performance models capable of handling both English and Chinese tasks while maintaining strong reasoning and conversational abilities. TigerBot models are based on modern transformer architectures and are trained on large datasets that cover multiple domains and languages. The project provides both base... -
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PyTorch-Tutorial-2nd
CV, NLP, LLM project applications, and advanced engineering deployment
PyTorch-Tutorial-2nd is an open-source educational repository that provides structured tutorials for learning deep learning with the PyTorch framework. The project serves as a practical companion to a second edition of a PyTorch learning guide and is designed to help learners understand neural network concepts through hands-on coding examples. The repository covers a wide range of topics including tensor operations, neural network construction, model training workflows, and optimization... -
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OpenCompass
OpenCompass is an LLM evaluation platform
Just like a compass guides us on our journey, OpenCompass will guide you through the complex landscape of evaluating large language models. With its powerful algorithms and intuitive interface, OpenCompass makes it easy to assess the quality and effectiveness of your NLP models. OpenCompass is a one-stop platform for large model evaluation, aiming to provide a fair, open, and reproducible benchmark for large model evaluation. Pre-support for 20+ HuggingFace and API models, a model evaluation scheme of 50+ datasets with about 300,000 questions, comprehensively evaluating the capabilities of the models in five dimensions. ... -
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Chinese-LLaMA-Alpaca 2
Chinese LLaMA-2 & Alpaca-2 Large Model Phase II Project
This project is developed based on the commercially available large model Llama-2 released by Meta. It is the second phase of the Chinese LLaMA&Alpaca large model project. The Chinese LLaMA-2 base model and the Alpaca-2 instruction fine-tuning large model are open-sourced. These models expand and optimize the Chinese vocabulary on the basis of the original Llama-2, use large-scale Chinese data for incremental pre-training, and further improve the basic semantics and command understanding of... -
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YAYI
Repo for YaYi Chinese LLMs based on LlaMA2 & BLOOM
YAYI is an open-source large language model project developed to provide a multilingual conversational AI system capable of performing a wide variety of natural language processing tasks. The model is trained on diverse datasets covering multiple languages and domains so that it can support applications ranging from dialogue systems to text analysis and knowledge retrieval. The architecture is based on transformer-style language models optimized for conversational understanding and... -
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Autolabel
Label, clean and enrich text datasets with LLMs
Autolabel is a Python library to label, clean and enrich datasets with Large Language Models (LLMs). Autolabel data for NLP tasks such as classification, question-answering and named entity recognition, entity matching and more. Seamlessly use commercial and open-source LLMs from providers such as OpenAI, Anthropic, HuggingFace, Google and more. -
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Chinese Llama 2 7B
The first Chinese LLaMA2 model in the open source community
Chinese Llama 2 7B is an open-source large language model adapted from the LLaMA-2 architecture and optimized for Chinese and bilingual Chinese-English applications. The project provides a version of LLaMA-2 that has been further trained on Chinese data so it can better understand and generate text in Chinese while maintaining compatibility with the original model ecosystem. In addition to the model weights, the repository also includes supervised fine-tuning datasets and training resources... -
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Doctor Dignity
Doctor Dignity is an LLM that can pass the US Medical Licensing Exam
...It emphasizes a humane UX: plain-language prompts, de-jargonized outputs, and guardrails that nudge users toward professional care when needed. The code is designed to be hackable rather than production-grade, giving learners a chance to experiment with NLP flows and lightweight back-end components. It also highlights privacy-aware patterns and cautions that this kind of software must not replace licensed medical advice. As a teaching and ideation vehicle, the project invites contributors to iterate on intent classification, response templates, and safe-use boundaries. -
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GLM-130B
GLM-130B: An Open Bilingual Pre-Trained Model (ICLR 2023)
GLM-130B is an open bilingual (English and Chinese) dense language model with 130 billion parameters, released by the Tsinghua KEG Lab and collaborators as part of the General Language Model (GLM) series. It is designed for large-scale inference and supports both left-to-right generation and blank filling, making it versatile across NLP tasks. Trained on over 400 billion tokens (200B English, 200B Chinese), it achieves performance surpassing GPT-3 175B, OPT-175B, and BLOOM-176B on multiple benchmarks, while also showing significant improvements on Chinese datasets compared to other large models. The model supports efficient inference via INT8 and INT4 quantization, reducing hardware requirements from 8× A100 GPUs to as little as a single server with 4× RTX 3090s. ... -
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Chinese-LLaMA-Alpaca-2 v2.0
Chinese LLaMA & Alpaca large language model + local CPU/GPU training
This project has open-sourced the Chinese LLaMA model and the Alpaca large model with instruction fine-tuning to further promote the open research of large models in the Chinese NLP community. Based on the original LLaMA , these models expand the Chinese vocabulary and use Chinese data for secondary pre-training, which further improves the basic semantic understanding of Chinese. At the same time, the Chinese Alpaca model further uses Chinese instruction data for fine-tuning, which significantly improves the model's ability to understand and execute instructions. -
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Emb-GAM
An interpretable and efficient predictor using pre-trained models
Deep learning models have achieved impressive prediction performance but often sacrifice interpretability, a critical consideration in high-stakes domains such as healthcare or policymaking. In contrast, generalized additive models (GAMs) can maintain interpretability but often suffer from poor prediction performance due to their inability to effectively capture feature interactions. In this work, we aim to bridge this gap by using pre-trained neural language models to extract embeddings for...
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