mcp-google-sheets

{ "Run inference on 100,000+ open ML models for NLP, vision, and audio tasks": "Run inference on 100,000+ open ML models for NLP, vision, and audio tasks", "Your Hugging Face API token (get it from https://huggingface.co/settings/tokens)": "Your Hugging Face API token (get it from https://huggingface.co/settings/tokens)", "Document Question Answering": "Document Question Answering", "Language Translation": "Language Translation", "Text Classification": "Text Classification", "Text Summarization": "Text Summarization", "Chat Completion": "Chat Completion", "Create Image": "Create Image", "Object Detection": "Object Detection", "Image Classification": "Image Classification", "Answer questions from document images using Hugging Face models": "Answer questions from document images using Hugging Face models", "Translate text between languages using specialized Hugging Face translation models": "Translate text between languages using specialized Hugging Face translation models", "Classify text into categories using Hugging Face models - includes zero-shot classification for custom categories": "Classify text into categories using Hugging Face models - includes zero-shot classification for custom categories", "Generate abstractive summaries of long text using Hugging Face models - optimized for business content": "Generate abstractive summaries of long text using Hugging Face models - optimized for business content", "Generate assistant replies using chat-style LLMs - perfect for FAQ bots, support agents, and content generation": "Generate assistant replies using chat-style LLMs - perfect for FAQ bots, support agents, and content generation", "Generate stunning images from text prompts using state-of-the-art diffusion models - perfect for marketing, product design, and creative content": "Generate stunning images from text prompts using state-of-the-art diffusion models - perfect for marketing, product design, and creative content", "Detect and locate objects in images with precise bounding boxes - perfect for inventory management, content moderation, and automated tagging": "Detect and locate objects in images with precise bounding boxes - perfect for inventory management, content moderation, and automated tagging", "Classify images with pre-trained models or custom categories - perfect for content moderation, automated tagging, and smart asset management": "Classify images with pre-trained models or custom categories - perfect for content moderation, automated tagging, and smart asset management", "Model": "Model", "Document Image": "Document Image", "Question": "Question", "Number of Answers": "Number of Answers", "Max Answer Length": "Max Answer Length", "Handle Impossible Answers": "Handle Impossible Answers", "OCR Language": "OCR Language", "Use Cache": "Use Cache", "Wait for Model": "Wait for Model", "Translation Model": "Translation Model", "Or Enter Custom Model ID": "Or Enter Custom Model ID", "Text to Translate": "Text to Translate", "Source Language (Optional)": "Source Language (Optional)", "Target Language (Optional)": "Target Language (Optional)", "Clean Up Extra Spaces": "Clean Up Extra Spaces", "Max Translation Length": "Max Translation Length", "Classification Type": "Classification Type", "Zero-Shot Model": "Zero-Shot Model", "Custom Categories": "Custom Categories", "Pre-trained Model": "Pre-trained Model", "Search Models": "Search Models", "Text to Classify": "Text to Classify", "Number of Results": "Number of Results", "Output Function": "Output Function", "Content Type": "Content Type", "Summarization Model": "Summarization Model", "Text to Summarize": "Text to Summarize", "Summary Length": "Summary Length", "Custom Min Length": "Custom Min Length", "Custom Max Length": "Custom Max Length", "Truncation Strategy": "Truncation Strategy", "Use Case": "Use Case", "Chat Model": "Chat Model", "Conversation Mode": "Conversation Mode", "User Message": "User Message", "System Prompt (Optional)": "System Prompt (Optional)", "Conversation History": "Conversation History", "Response Template": "Response Template", "Response Length": "Response Length", "Custom Max Tokens": "Custom Max Tokens", "Creativity Level": "Creativity Level", "Response Variety": "Response Variety", "Stop Sequences (Optional)": "Stop Sequences (Optional)", "Repetition Penalty": "Repetition Penalty", "Topic Diversity": "Topic Diversity", "Image Generation Model": "Image Generation Model", "Text Prompt": "Text Prompt", "Aspect Ratio": "Aspect Ratio", "Custom Width": "Custom Width", "Custom Height": "Custom Height", "Negative Prompt": "Negative Prompt", "Quality vs Speed": "Quality vs Speed", "Custom Inference Steps": "Custom Inference Steps", "Guidance Scale": "Guidance Scale", "Seed (Optional)": "Seed (Optional)", "Scheduler": "Scheduler", "Detection Model": "Detection Model", "Image to Analyze": "Image to Analyze", "Confidence Threshold": "Confidence Threshold", "Max Detections": "Max Detections", "Detection Filter": "Detection Filter", "Output Format": "Output Format", "Classification Mode": "Classification Mode", "Classification Model": "Classification Model", "Image Source": "Image Source", "Image File": "Image File", "Image URL": "Image URL", "Classification Template": "Classification Template", "Hugging Face document question answering model": "Hugging Face document question answering model", "Image of the document to analyze (invoice, contract, etc.)": "Image of the document to analyze (invoice, contract, etc.)", "Question to ask about the document (e.g., 'What is the invoice total?')": "Question to ask about the document (e.g., 'What is the invoice total?')", "Number of top answers to return": "Number of top answers to return", "Maximum length of predicted answers": "Maximum length of predicted answers", "Whether to accept 'impossible' as an answer when no answer is found": "Whether to accept 'impossible' as an answer when no answer is found", "Language to use for OCR text extraction": "Language to use for OCR text extraction", "Use cached results if available": "Use cached results if available", "Wait for model to load if not ready": "Wait for model to load if not ready", "Select a translation model or search from 7000+ available models": "Select a translation model or search from 7000+ available models", "Alternative: Enter any Hugging Face translation model ID directly (e.g., Helsinki-NLP/opus-mt-ja-en)": "Alternative: Enter any Hugging Face translation model ID directly (e.g., Helsinki-NLP/opus-mt-ja-en)", "The text content you want to translate": "The text content you want to translate", "Source language code (e.g., \"en\", \"es\", \"fr\"). Only needed for multilingual models that support multiple language pairs.": "Source language code (e.g., \"en\", \"es\", \"fr\"). Only needed for multilingual models that support multiple language pairs.", "Target language code (e.g., \"fr\", \"de\", \"zh\"). Only needed for multilingual models that support multiple language pairs.": "Target language code (e.g., \"fr\", \"de\", \"zh\"). Only needed for multilingual models that support multiple language pairs.", "Remove potential extra spaces in the translation output": "Remove potential extra spaces in the translation output", "Maximum length of the translated text (leave empty for default)": "Maximum length of the translated text (leave empty for default)", "Use cached results if available for faster responses": "Use cached results if available for faster responses", "Wait for model to load if not immediately available": "Wait for model to load if not immediately available", "Choose your classification approach": "Choose your classification approach", "Model for classifying into your custom categories": "Model for classifying into your custom categories", "Enter categories separated by commas (e.g., \"customer support, sales inquiry, spam, billing question\")": "Enter categories separated by commas (e.g., \"customer support, sales inquiry, spam, billing question\")", "Select a specialized pre-trained classification model": "Select a specialized pre-trained classification model", "Search from all available text classification models": "Search from all available text classification models", "The text content you want to classify": "The text content you want to classify", "Number of top predictions to return": "Number of top predictions to return", "How to calculate confidence scores": "How to calculate confidence scores", "Use cached results for faster responses": "Use cached results for faster responses", "What type of content are you summarizing?": "What type of content are you summarizing?", "Select the best model for your content type": "Select the best model for your content type", "The long text content you want to summarize (most models work best with 512-1024 tokens)": "The long text content you want to summarize (most models work best with 512-1024 tokens)", "How long should the summary be?": "How long should the summary be?", "Minimum number of tokens for the summary": "Minimum number of tokens for the summary", "Maximum number of tokens for the summary": "Maximum number of tokens for the summary", "Remove extra spaces and clean up formatting": "Remove extra spaces and clean up formatting", "How to handle text that exceeds model limits": "How to handle text that exceeds model limits", "What type of chat assistant are you building?": "What type of chat assistant are you building?", "Select the best model for your use case": "Select the best model for your use case", "How do you want to build the conversation?": "How do you want to build the conversation?", "The user message or question to respond to": "The user message or question to respond to", "Instructions for how the assistant should behave": "Instructions for how the assistant should behave", "Previous messages in the conversation (for multi-turn chat)": "Previous messages in the conversation (for multi-turn chat)", "Pre-built templates for common business scenarios": "Pre-built templates for common business scenarios", "How long should the response be?": "How long should the response be?", "Maximum number of tokens to generate": "Maximum number of tokens to generate", "How creative should responses be? (0.1 = focused, 1.0 = creative)": "How creative should responses be? (0.1 = focused, 1.0 = creative)", "Controls response diversity (0.1 = focused, 1.0 = varied)": "Controls response diversity (0.1 = focused, 1.0 = varied)", "Text sequences that will stop generation": "Text sequences that will stop generation", "Reduce repetitive responses (-2.0 to 2.0)": "Reduce repetitive responses (-2.0 to 2.0)", "Encourage diverse topics (-2.0 to 2.0)": "Encourage diverse topics (-2.0 to 2.0)", "Use cached responses for identical requests": "Use cached responses for identical requests", "What type of image generation do you need?": "What type of image generation do you need?", "Describe the image you want to generate. Be specific about style, colors, composition, and details.": "Describe the image you want to generate. Be specific about style, colors, composition, and details.", "Choose the dimensions for your image": "Choose the dimensions for your image", "Width in pixels (64-1024)": "Width in pixels (64-1024)", "Height in pixels (64-1024)": "Height in pixels (64-1024)", "Describe what you DON'T want in the image (blur, low quality, distorted, etc.)": "Describe what you DON'T want in the image (blur, low quality, distorted, etc.)", "Balance between image quality and generation time": "Balance between image quality and generation time", "Number of denoising steps (1-100)": "Number of denoising steps (1-100)", "How closely to follow the prompt (1-20). Higher values = more prompt adherence but may reduce creativity.": "How closely to follow the prompt (1-20). Higher values = more prompt adherence but may reduce creativity.", "Set a seed for reproducible results. Leave empty for random generation.": "Set a seed for reproducible results. Leave empty for random generation.", "Advanced: Choose the noise scheduler algorithm": "Advanced: Choose the noise scheduler algorithm", "What type of object detection do you need?": "What type of object detection do you need?", "Select the best model for your detection task": "Select the best model for your detection task", "Upload an image for object detection. Supports JPG, PNG, WebP formats.": "Upload an image for object detection. Supports JPG, PNG, WebP formats.", "Minimum confidence score for detections (0.1-0.9). Higher values = fewer but more accurate detections.": "Minimum confidence score for detections (0.1-0.9). Higher values = fewer but more accurate detections.", "Maximum number of objects to detect (1-100)": "Maximum number of objects to detect (1-100)", "How to handle detection results": "How to handle detection results", "How to structure the detection results": "How to structure the detection results", "How do you want to classify your images?": "How do you want to classify your images?", "What type of image classification do you need?": "What type of image classification do you need?", "How do you want to provide the image?": "How do you want to provide the image?", "Upload an image file for classification (JPG, PNG, WebP)": "Upload an image file for classification (JPG, PNG, WebP)", "URL of the image to classify": "URL of the image to classify", "Enter the categories you want to classify the image into (e.g., \"dog\", \"cat\", \"bird\")": "Enter the categories you want to classify the image into (e.g., \"dog\", \"cat\", \"bird\")", "Template for classification (advanced). Default: \"This image shows {}\"": "Template for classification (advanced). Default: \"This image shows {}\"", "Maximum number of classification results to return (1-20)": "Maximum number of classification results to return (1-20)", "Minimum confidence score for results (0.0-1.0)": "Minimum confidence score for results (0.0-1.0)", "How to structure the classification results": "How to structure the classification results", "impira/layoutlm-document-qa (Recommended)": "impira/layoutlm-document-qa (Recommended)", "microsoft/layoutlmv3-base": "microsoft/layoutlmv3-base", "nielsr/layoutlmv2-finetuned-docvqa": "nielsr/layoutlmv2-finetuned-docvqa", "English": "English", "Spanish": "Spanish", "French": "French", "German": "German", "Italian": "Italian", "Portuguese": "Portuguese", "🎯 Zero-Shot (Custom Categories)": "🎯 Zero-Shot (Custom Categories)", "📊 Pre-trained Models": "📊 Pre-trained Models", "🔍 Search All Models": "🔍 Search All Models", "🔥 Facebook BART-Large (5.4M downloads)": "🔥 Facebook BART-Large (5.4M downloads)", "🔥 DeBERTa TaskSource (904K downloads)": "🔥 DeBERTa TaskSource (904K downloads)", "🔥 DeBERTa MNLI-FEVER (668K downloads)": "🔥 DeBERTa MNLI-FEVER (668K downloads)", "🌍 DistilBERT Multilingual (520K downloads)": "🌍 DistilBERT Multilingual (520K downloads)", "😊 Sentiment: Twitter RoBERTa (3M downloads)": "😊 Sentiment: Twitter RoBERTa (3M downloads)", "😊 Sentiment: DistilBERT SST-2 (2.9M downloads)": "😊 Sentiment: DistilBERT SST-2 (2.9M downloads)", "🌍 Sentiment: Multilingual BERT (1.7M downloads)": "🌍 Sentiment: Multilingual BERT (1.7M downloads)", "💰 Finance: FinBERT Sentiment (1.5M downloads)": "💰 Finance: FinBERT Sentiment (1.5M downloads)", "💰 Finance: FinBERT Tone (1.4M downloads)": "💰 Finance: FinBERT Tone (1.4M downloads)", "🛡️ Hate Speech: RoBERTa (2M downloads)": "🛡️ Hate Speech: RoBERTa (2M downloads)", "🛡️ Toxicity: HateBERT (1.1M downloads)": "🛡️ Toxicity: HateBERT (1.1M downloads)", "🛡️ Toxicity: ToxDect RoBERTa (1.1M downloads)": "🛡️ Toxicity: ToxDect RoBERTa (1.1M downloads)", "🎧 Customer Service: Banking Intent": "🎧 Customer Service: Banking Intent", "📧 Spam: SMS Classification": "📧 Spam: SMS Classification", "Softmax (Recommended)": "Softmax (Recommended)", "Sigmoid": "Sigmoid", "None (Raw Scores)": "None (Raw Scores)", "📰 News Articles & Blog Posts": "📰 News Articles & Blog Posts", "📧 Emails & Support Tickets": "📧 Emails & Support Tickets", "🎯 Meetings & Conversations": "🎯 Meetings & Conversations", "📚 General Text & Documents": "📚 General Text & Documents", "🏥 Medical & Scientific": "🏥 Medical & Scientific", "🌍 Multilingual Content": "🌍 Multilingual Content", "📝 Brief (30-80 words)": "📝 Brief (30-80 words)", "📄 Medium (80-150 words)": "📄 Medium (80-150 words)", "📚 Detailed (150-300 words)": "📚 Detailed (150-300 words)", "⚙️ Custom Length": "⚙️ Custom Length", "Do Not Truncate": "Do Not Truncate", "Longest First": "Longest First", "Only First": "Only First", "Only Second": "Only Second", "FAQ & Customer Support": "FAQ & Customer Support", "Content Generation & Writing": "Content Generation & Writing", "General Conversation": "General Conversation", "Search All Models": "Search All Models", "Single Message (Simple Q&A)": "Single Message (Simple Q&A)", "Multi-turn Conversation": "Multi-turn Conversation", "Template-based Response": "Template-based Response", "Customer Support Agent": "Customer Support Agent", "FAQ Assistant": "FAQ Assistant", "Content Writer": "Content Writer", "Email Responder": "Email Responder", "E-commerce Assistant": "E-commerce Assistant", "Brief (50-100 tokens)": "Brief (50-100 tokens)", "Normal (100-200 tokens)": "Normal (100-200 tokens)", "Detailed (200-400 tokens)": "Detailed (200-400 tokens)", "Custom": "Custom", "Fast Generation (Quick Prototypes)": "Fast Generation (Quick Prototypes)", "High Quality (Marketing & Print)": "High Quality (Marketing & Print)", "Business Content (Products & Brands)": "Business Content (Products & Brands)", "📱 Portrait (512×768) - Social Media": "📱 Portrait (512×768) - Social Media", "🖥️ Landscape (768×512) - Banners": "🖥️ Landscape (768×512) - Banners", "⬜ Square (512×512) - Profile Pictures": "⬜ Square (512×512) - Profile Pictures", "📺 Wide (1024×576) - Headers": "📺 Wide (1024×576) - Headers", "⚙️ Custom Dimensions": "⚙️ Custom Dimensions", "⚡ Fast (10-20 steps)": "⚡ Fast (10-20 steps)", "⚖️ Balanced (20-30 steps)": "⚖️ Balanced (20-30 steps)", "🎯 High Quality (30-50 steps)": "🎯 High Quality (30-50 steps)", "🏆 Maximum Quality (50+ steps)": "🏆 Maximum Quality (50+ steps)", "⚙️ Custom Steps": "⚙️ Custom Steps", "DPM++ 2M Karras (Recommended)": "DPM++ 2M Karras (Recommended)", "Euler A (Fast)": "Euler A (Fast)", "DDIM (Stable)": "DDIM (Stable)", "LMS (Classic)": "LMS (Classic)", "📋 General Objects (COCO Dataset)": "📋 General Objects (COCO Dataset)", "📊 Documents & Tables": "📊 Documents & Tables", "🛡️ Security & Monitoring": "🛡️ Security & Monitoring", "🏢 Business & Commerce": "🏢 Business & Commerce", "🎯 High Confidence Only (>0.7)": "🎯 High Confidence Only (>0.7)", "⚖️ Balanced Results (>0.5)": "⚖️ Balanced Results (>0.5)", "📊 All Detections (>0.1)": "📊 All Detections (>0.1)", "⚙️ Custom Threshold": "⚙️ Custom Threshold", "📋 Business Summary": "📋 Business Summary", "🔧 Technical Details": "🔧 Technical Details", "📊 Statistical Analysis": "📊 Statistical Analysis", "🌐 All Information": "🌐 All Information", "🏷️ Pre-trained Categories (Standard)": "🏷️ Pre-trained Categories (Standard)", "🎯 Custom Categories (Zero-shot)": "🎯 Custom Categories (Zero-shot)", "🛡️ Content Moderation & Safety": "🛡️ Content Moderation & Safety", "🏷️ General Image Tagging": "🏷️ General Image Tagging", "👤 People & Demographics": "👤 People & Demographics", "🎨 Creative & Media": "🎨 Creative & Media", "💼 Business & Commerce": "💼 Business & Commerce", "📎 Upload File": "📎 Upload File", "🔗 Image URL": "🔗 Image URL", "🌐 Comprehensive Report": "🌐 Comprehensive Report" }