Search Results for "programming languages learning"
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Showing 13 open source projects for "programming languages learning"
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Tabby
Self-hosted AI coding assistant
Tabby is an open-source, self-hosted AI coding assistant that provides code completion and suggestions within your preferred development environment. It enhances developer productivity by leveraging machine learning models to predict and generate code snippets. -
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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 from natural language descriptions, code translation, bug fixing, and explanation. ... -
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BAML
The AI framework that adds the engineering to prompt engineering
...This design allows developers to treat language model interactions as predictable software components rather than ad-hoc prompt strings. The framework enables developers to define prompt logic in a dedicated language while integrating it into applications written in various programming languages such as Python, TypeScript, Ruby, and Go. BAML also allows developers to specify which models are used for each prompt and how outputs should be validated or structured. By converting prompt engineering into a more formal programming workflow, the framework improves reliability, debugging, and maintainability of AI systems. -
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Qdrant
Vector Database for the next generation of AI applications
...With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications for matching, searching, recommending, and much more! Provides the OpenAPI v3 specification to generate a client library in almost any programming language. Alternatively, utilize ready-made client for Python or other programming languages with additional functionality. Implement a unique custom modification of the HNSW algorithm for the Approximate Nearest Neighbor Search. Search with a State-of-the-Art speed and apply search filters without compromising on results. Support additional payload associated with vectors. ... -
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5
Refact Agent
WebUI for Fine-Tuning and Self-hosting of Open-Source LLMs
Refact is an AI-powered code assistant designed to enhance software development workflows. It integrates with code editors and provides suggestions, refactoring assistance, and debugging insights. -
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PostgresML
The GPU-powered AI application database
PostgresML is a complete platform in a PostgreSQL extension. Build simpler, faster, and more scalable models right inside your database. Explore the SDK and test open source models in our hosted database. Combine and automate the entire workflow from embedding generation to indexing and querying for the simplest (and fastest) knowledge-based chatbot implementation. Leverage multiple types of natural language processing and machine learning models such as vector search and personalization... -
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rust-bert
Rust native ready-to-use NLP pipelines and transformer-based models
rust-bert is a Rust-based implementation of transformer-based natural language processing models that provides ready-to-use pipelines for tasks such as text classification, summarization, and question answering. The project ports many capabilities of the Hugging Face Transformers ecosystem into the Rust programming language. It allows developers to run state-of-the-art NLP models like BERT, GPT-2, and DistilBERT directly within Rust applications while maintaining high performance and memory efficiency. The library integrates with Rust machine learning infrastructure using crates such as tch-rs and ONNX Runtime for model execution. It also includes tokenization utilities, model architectures, and task-specific pipelines that simplify the development of NLP applications. ... -
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ort
Fast ML inference & training for ONNX models in Rust
ort is a high-performance Rust library that provides bindings to ONNX Runtime, enabling developers to run machine learning inference and training workflows directly within Rust applications using the standardized ONNX model format. It is designed to bridge the gap between modern machine learning frameworks and systems programming by offering a safe, ergonomic API for executing models originally built in ecosystems like PyTorch, TensorFlow, or scikit-learn. -
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Floneum
Instant, controllable, local pre-trained AI models in Rust
...Floneum supports a plugin architecture that allows external components to extend the platform while maintaining isolation and security. Many plugins can be written in different programming languages and compiled to WebAssembly modules, allowing them to run safely within the system. The platform is implemented primarily in Rust and emphasizes performance, modularity, and local execution. -
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10
bloop
bloop is a fast code search engine written in Rust
Bloop is an AI-powered code search tool designed to help developers quickly find relevant code snippets, documentation, and usage examples within large repositories. It provides natural language search capabilities and AI-enhanced recommendations for improving code discovery. -
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Luminal
Deep learning at the speed of light
Luminal is a framework designed to accelerate and simplify the development of systems-level data applications by using a typed, functional, and streaming-first approach. Instead of treating data processing as a series of ad-hoc scripts, Luminal models transformations as strongly typed building blocks that can be composed into reliable, scalable pipelines. The project emphasizes correctness and performance by requiring explicit types for the data flowing through transformations, reducing... -
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SIG Rust
Rust language bindings for TensorFlow
SIG Rust provides idiomatic Rust bindings for TensorFlow, making it possible for developers to work with TensorFlow functionality from within the Rust programming language. Rather than replacing TensorFlow itself, it acts as an integration layer that connects Rust applications to the TensorFlow C API. The repository is designed for developers who want Rust’s performance, safety, and systems programming strengths while still accessing TensorFlow’s machine learning capabilities. It includes setup instructions that explain how the crate can automatically download or compile the required TensorFlow shared libraries, which lowers the barrier to getting started. ... -
13
Weld
High-performance runtime for data analytics applications
...The language includes built-in constructs for expressing data-parallel operations, enabling efficient execution on modern hardware architectures. By combining operations from multiple libraries into a single optimized execution plan, Weld can significantly improve performance in analytics and machine learning pipelines.
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