3 Repos
Terminal-based conversational interfaces for interacting with AI models.
Distinct from Chat Interfaces: Focuses specifically on the terminal/CLI implementation rather than general web-based chat interfaces.
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ParlAI is a conversational AI research framework designed for training, evaluating, and sharing dialogue models using a unified interface for datasets and agents. It functions as a PyTorch-based training platform and a dialogue data collection system, providing a centralized model zoo for the distribution of versioned pretrained agents. The project distinguishes itself through a knowledge-grounded retrieval system that combines dense and sparse indexing to ground responses in external information. It also provides a comprehensive infrastructure for gathering human-AI interaction data via inte
Provides a terminal-based conversational interface for interacting with trained AI models in real time.
OpenChatKit is a training and inference toolkit for large language models. It provides a comprehensive set of tools for managing the model lifecycle, including a fine-tuning pipeline, a model weight converter, and a command-line interface for interacting with conversational agents. The toolkit features a framework for retrieval augmented generation, allowing models to incorporate relevant context from external vector indices. It also includes utilities for converting trained model checkpoints into formats compatible with standard inference libraries. The project covers conversational AI trai
Ships a terminal-based environment for testing model performance and interacting with conversational agents.
llama-rs ist eine Inferenz-Engine für lokale Large Language Models, die in Rust implementiert ist. Sie ermöglicht die Ausführung von Modellberechnungen auf lokaler Hardware, um Textantworten aus Benutzer-Prompts zu generieren. Das Projekt nutzt Rust-basierte Tensor-Operationen und Direct-Memory-Modell-Mapping, um High-Performance-Lineare-Algebra und effizientes Laden von Gewichten zu handhaben. Es integriert Weight-Quantization, um den Speicherbedarf von Modellen durch Konvertierung hochpräziser Gewichte in kleinere Formate zu reduzieren. Das System enthält ein Kommandozeilen-Interface für interaktive Chat-Sitzungen und einmalige Prompts, zusammen mit Datei-basierter Sitzungspersistenz, um Konversationsverläufe zu speichern und wiederherzustellen. Es bietet zudem Utilities zum Abrufen von Tokenizer-Konfigurationen von Remote-Hubs sowie Tools zur Berechnung von Perplexity-Scores, um die Modellleistung zu evaluieren.
Offers a terminal-based conversational interface for interacting with local AI models.