Open LLM(CohereForAI/c4ai-command-r7b-12-2024) and RAG
Analyze similarity of patent claims and responses
Experiment with and compare different tokenizers
Generative Tasks Evaluation of Arabic LLMs
Identify named entities in text
Display and explore model leaderboards and chat history
Explore and interact with HuggingFace LLM APIs using Swagger UI
fake news detection using distilbert trained on liar dataset
Playground for NuExtract-v1.5
Detect AI-generated texts with precision
Detect if text was generated by GPT-2
Rerank documents based on a query
Classify patent abstracts into subsectors
RAGOndevice AI is a cutting-edge artificial intelligence tool designed for text analysis and interactive AI chat. It leverages the power of Open LLM (CohereForAI/c4ai-command-r7b-12-2024) and RAG (Retrieval-Augmented Generation) technology to analyze documents and provide insightful responses. Users can upload files, engage in AI-powered conversations, and uncover valuable information from their data.
• Document Analysis: Process and analyze text files for extracts and insights.
• AI Chat Interface: Engage in natural-sounding conversations with the AI.
• RAG Technology: Combines document retrieval with AI generation for accurate responses.
• Support for Multiple File Types: Process PDF, Word, Text, and other document formats.
• Privacy-Focused: Runs entirely on-device, ensuring your data stays private.
• Multi-Language Support: Work with documents in various languages.
• Customizable Outputs: Fine-tune AI responses based on specific needs.
• Efficient Processing: Handles large documents with minimal latency.
What file types does RAGOndevice AI support?
RAGOndevice AI supports PDF, Word, Text, and several other document formats for analysis.
Is my data private when using RAGOndevice AI?
Yes, RAGOndevice AI runs entirely on your device, ensuring your data remains private and secure.
What does "RAG" mean in RAGOndevice AI?
RAG stands for Retrieval-Augmented Generation, a technology that combines document retrieval with AI generation to provide accurate and context-specific responses.