Search Results for "python language" - Page 3
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Showing 535 open source projects for "python language"
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MCP Neo4j
Model Context Protocol with Neo4j
An implementation of the Model Context Protocol with Neo4j, enabling natural language interactions with Neo4j databases and facilitating operations such as schema retrieval and Cypher query execution. -
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Xiyan MCP Server
A Model Context Protocol (MCP) server
The XiYan MCP Server is a Model Context Protocol (MCP) server that enables natural language queries to databases, powered by XiYan-SQL, a state-of-the-art text-to-SQL model. It allows users to interact with databases using conversational language, simplifying data retrieval processes. -
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Vanna
Chat with your SQL database
Vanna.AI is an AI-powered tool for natural language database querying, enabling users to interact with databases using simple English queries. It converts natural language questions into SQL queries, making data access more intuitive for non-technical users. -
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DeepSparse
Sparsity-aware deep learning inference runtime for CPUs
A sparsity-aware enterprise inferencing system for AI models on CPUs. Maximize your CPU infrastructure with DeepSparse to run performant computer vision (CV), natural language processing (NLP), and large language models (LLMs). -
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MegaParse
File Parser optimised for LLM Ingestion with no loss
MegaParse is a file parser optimized for Large Language Model (LLM) ingestion, ensuring no loss of information. It efficiently parses various document formats, such as PDFs, DOCX, and PPTX, converting them into formats ideal for processing by LLMs. This tool is essential for applications that require accurate and comprehensive data extraction from diverse document types. -
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BudouX
Standalone, small, language-neutral
Standalone. Small. Language-neutral. BudouX is the successor to Budou, the machine learning-powered line break organizer tool. It is standalone. It works with no dependency on third-party word segmenters such as Google cloud natural language API. It is small. It takes only around 15 KB including its machine learning model. It's reasonable to use it even on the client-side. It is language-neutral. You can train a model for any language by feeding a dataset to BudouX’s training... -
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ChatGLM-6B
ChatGLM-6B: An Open Bilingual Dialogue Language Model
ChatGLM-6B is an open bilingual (Chinese + English) conversational language model based on the GLM architecture, with approximately 6.2 billion parameters. The project provides inference code, demos (command line, web, API), quantization support for lower memory deployment, and tools for finetuning (e.g., via P-Tuning v2). It is optimized for dialogue and question answering with a balance between performance and deployability in consumer hardware settings. Support for quantized inference... -
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Open Interpreter
A natural language interface for computers
Open Interpreter is an open-source tool that provides a natural-language interface for interacting with your computer. It lets large language models (LLMs) run code locally (Python, JavaScript, shell, etc.), enabling you to ask your computer to do tasks like data analysis, file manipulation, browsing, etc. in human terms (“chat with your computer”), with safeguards. Runs locally or via configured remote LLM servers/inference backends, giving flexibility to use models you trust or have locally. ... -
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NeMo Curator
Scalable data pre processing and curation toolkit for LLMs
NeMo Curator is a Python library specifically designed for fast and scalable dataset preparation and curation for large language model (LLM) use-cases such as foundation model pretraining, domain-adaptive pretraining (DAPT), supervised fine-tuning (SFT) and paramter-efficient fine-tuning (PEFT). It greatly accelerates data curation by leveraging GPUs with Dask and RAPIDS, resulting in significant time savings. -
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Kaleidoscope-SDK
User toolkit for analyzing and interfacing with Large Language Models
kaleidoscope-sdk is a Python module used to interact with large language models hosted via the Kaleidoscope service available at: https://github.com/VectorInstitute/kaleidoscope. It provides a simple interface to launch LLMs on an HPC cluster, asking them to perform basic features like text generation, but also retrieve intermediate information from inside the model, such as log probabilities and activations. -
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OpenLLM
Operating LLMs in production
...Serve LLMs over RESTful API or gRPC with one command, query via WebUI, CLI, our Python/Javascript client, or any HTTP client. -
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Phi-3-MLX
Phi-3.5 for Mac: Locally-run Vision and Language Models
Phi-3-Vision-MLX is an Apple MLX (machine learning on Apple silicon) implementation of Phi-3 Vision, a lightweight multi-modal model designed for vision and language tasks. It focuses on running vision-language AI efficiently on Apple hardware like M1 and M2 chips. -
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MindNLP
Easy-to-use and high-performance NLP and LLM framework
MindNLP is a natural language processing library built on the MindSpore framework, providing tools and models for various NLP tasks. -
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Chonkie
The no-nonsense RAG chunking library
Chonkie is an AI-powered framework designed for building conversational agents and chatbots with natural language understanding and multi-turn conversation support. -
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LangChain.js
Building applications with LLMs through composability
...This is built to integrate as seamlessly as possible with the LangChain Python package. Specifically, this means all objects (prompts, LLMs, chains, etc) are designed in a way where they can be serialized and shared between languages. -
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VibeThinker
Diversity-driven optimization and large-model reasoning ability
VibeThinker is a compact but high-capability open-source language model released by WeiboAI (Sina AI Lab). It contains about 1.5 billion parameters, far smaller than many “frontier” models, yet it is explicitly optimized for reasoning, mathematics, and code generation tasks rather than general open-domain chat. The innovation lies in its training methodology: the team uses what they call the Spectrum-to-Signal Principle (SSP), where a first stage emphasizes diversity of reasoning paths (the... -
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PaperAI
Semantic search and workflows for medical/scientific papers
PaperAI is an open-source framework for searching and analyzing scientific papers, particularly useful for researchers looking to extract insights from large-scale document collections. -
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CodeGeeX4
CodeGeeX4-ALL-9B, a versatile model for all AI software development
CodeGeeX4 is the fourth-generation open source multilingual code large language model (LLM) developed by ZhipuAI. Designed as a powerful AI coding assistant, it supports over 100 programming languages and has been trained on a massive code and natural language corpus. Compared to its predecessors, CodeGeeX4 introduces improved reasoning, stronger alignment with developer needs, and better performance on real-world programming benchmarks. It supports tasks such as code completion, generation... -
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DeepSeek VL2
Mixture-of-Experts Vision-Language Models for Advanced Multimodal
DeepSeek-VL2 is DeepSeek’s vision + language multimodal model—essentially the next-gen successor to their first vision-language models. It combines image and text inputs into a unified embedding / reasoning space so that you can query with text and image jointly (e.g. “What’s going on in this scene?” or “Generate a caption appropriate to context”). The model supports both image understanding (vision tasks) and multimodal reasoning, and is likely used as a component in agent systems to... -
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PrivateGPT
Interact with your documents using the power of GPT
PrivateGPT is a production-ready, privacy-first AI system that allows querying of uploaded documents using LLMs, operating completely offline in your own environment. It provides contextual generative AI capabilities without sending data externally. Now maintained under Zylon.ai with enterprise deployment options (air gapped, cloud, or on-prem). -
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LiteLLM
lightweight package to simplify LLM API calls
Call all LLM APIs using the OpenAI format [Anthropic, Huggingface, Cohere, Azure OpenAI etc.] liteLLM supports streaming the model response back, pass stream=True to get a streaming iterator in response. Streaming is supported for OpenAI, Azure, Anthropic, and Huggingface models. -
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PEFT
State-of-the-art Parameter-Efficient Fine-Tuning
Parameter-Efficient Fine-Tuning (PEFT) methods enable efficient adaptation of pre-trained language models (PLMs) to various downstream applications without fine-tuning all the model's parameters. Fine-tuning large-scale PLMs is often prohibitively costly. In this regard, PEFT methods only fine-tune a small number of (extra) model parameters, thereby greatly decreasing the computational and storage costs. Recent State-of-the-Art PEFT techniques achieve performance comparable to that of full... -
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DeepSeek R1
Open-source, high-performance AI model with advanced reasoning
DeepSeek-R1 is an open-source large language model developed by DeepSeek, designed to excel in complex reasoning tasks across domains such as mathematics, coding, and language. DeepSeek R1 offers unrestricted access for both commercial and academic use. The model employs a Mixture of Experts (MoE) architecture, comprising 671 billion total parameters with 37 billion active parameters per token, and supports a context length of up to 128,000 tokens. DeepSeek-R1's training regimen uniquely... -
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smolagents
Agents write python code to call tools and orchestrate other agents
This library is the simplest framework out there to build powerful agents. We provide our definition in this page, where you’ll also find tips for when to use them or not (spoilers: you’ll often be better off without agents). smolagents is a lightweight framework for building AI agents using large language models (LLMs). It simplifies the development of AI-driven applications by providing tools to create, train, and deploy language model-based agents. -
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GLM-4.5
GLM-4.5: Open-source LLM for intelligent agents by Z.ai
GLM-4.5 is a cutting-edge open-source large language model designed by Z.ai for intelligent agent applications. The flagship GLM-4.5 model has 355 billion total parameters with 32 billion active parameters, while the compact GLM-4.5-Air version offers 106 billion total parameters and 12 billion active parameters. Both models unify reasoning, coding, and intelligent agent capabilities, providing two modes: a thinking mode for complex reasoning and tool usage, and a non-thinking mode for...
