AI Directory : AI Chatbot, Large Language Models (LLMs)
What is OpenChatKit?
OpenChatKit is an open-source project that provides a powerful base to create both specialized and general-purpose chatbots for various applications.
How to use OpenChatKit?
To use OpenChatKit, you can visit the OpenChatKit website and try out the demo. You can also access the source code, model weights, and training datasets on GitHub. For more information on how to use OpenChatKit and give feedback, you can join the OpenChatKit community on GitHub, Discord, Twitter, and Medium.
OpenChatKit's Core Features
Instruction-tuned large language model
Various natural language tasks handling
Large dataset
Extensible retrieval system
Live-updating source
Sample code available
OpenChatKit's Use Cases
Dialogue
Question answering
Classification
Extraction
Summarization
FAQ from OpenChatKit
What is OpenChatKit?
OpenChatKit is an open-source project that provides a powerful base to create both specialized and general-purpose chatbots for various applications.
How to use OpenChatKit?
To use OpenChatKit, you can visit the OpenChatKit website and try out the demo. You can also access the source code, model weights, and training datasets on GitHub. For more information on how to use OpenChatKit and give feedback, you can join the OpenChatKit community on GitHub, Discord, Twitter, and Medium.
What is OpenChatKit and what does it provide?
OpenChatKit is an open-source project that provides a powerful base to create both specialized and general purpose chatbots for various applications. It consists of four key components: an instruction-tuned large language model, customization recipes to fine-tune the model, an extensible retrieval system to augment the model with live-updating information, and a moderation model to filter inappropriate or out-of-domain questions.
Who are the collaborators behind OpenChatKit and the training datasets?
OpenChatKit is a collaboration between Together, LAION, and Ontocord. They created the OIG-43M dataset, a collection of 43 million high-quality instructions for conversational interactions, and the moderation dataset, a collection of inappropriate questions for chatbots.
How can I try out OpenChatKit and give feedback?
You can try out OpenChatKit on the OpenChatKit website and give feedback through the OpenChatKit feedback app. You can also join the OpenChatKit community on GitHub, Discord, Twitter, and Medium to share your ideas, suggestions, and questions.
What is the base model of OpenChatKit and how is it fine-tuned?
The base model of OpenChatKit is GPT-NeoXT-Chat-Base-20B, a 20 billion parameter large language model based on EleutherAI’s GPT-NeoX model. It is fine-tuned with the OIG-43M dataset, focusing on several tasks such as multi-turn dialogue, question answering, classification, extraction, and summarization.
How does OpenChatKit perform on different natural language tasks?
OpenChatKit performs well on a broad set of natural language tasks, especially those involving question and answering, extraction, and classification. However, there are also areas where OpenChatKit needs improvement, such as knowledge-based closed question and answering, coding tasks, repetition, context switching, and creative writing and longer answers.
How can I cite or reference OpenChatKit or the training datasets in my work?
You can cite or reference OpenChatKit or the training datasets in your work by using the provided BibTeX entries in the GitHub repository.
How does OpenChatKit compare with other large language models or chatbots?
OpenChatKit compares favorably with other large language models or chatbots in terms of its versatility, customizability, and extensibility. It can handle a wide range of natural language tasks with high performance, and it can be fine-tuned and adapted for specific applications or domains with the provided tools and recipes.
What is the license of OpenChatKit and how can I modify or inspect the weights?
OpenChatKit is licensed under the Apache License 2.0, which allows you to freely use, modify, and distribute the software. You can also inspect the weights of the model using the Hugging Face Transformers library or the Jupyter notebooks provided in the GitHub repository.
How can I access the source code, model weights, and training datasets of OpenChatKit?
You can access the source code, model weights, and training datasets of OpenChatKit on GitHub. The model weights and datasets can also be downloaded from Hugging Face.