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Fuyu-8B AI technology page Top Builders

Explore the top contributors showcasing the highest number of Fuyu-8B AI technology page app submissions within our community.

Fuyu-8B Model

Fuyu-8B, developed by Adept AI, is a cutting-edge multi-modal text and image transformer tailored specifically for digital agents. Released in Month XX, 20XX, this model is optimized for swift response times (under 100 milliseconds) while excelling in a range of image-related tasks.

General
AuthorAdept AI
RepositoryFuyu-8B on HuggingFace
TypeMulti-modal text and image transformer

Model Capabilities

Fuyu-8B is engineered to empower digital agents with a diverse set of capabilities, including:

  • Image-Related Queries: Efficient handling of image-related queries and tasks.
  • Fine-Grained Image Localization: Precision in identifying and localizing elements within images.
  • Rapid Responses for Large Images: Swift and accurate responses even with large-sized images.

Technology Tutorials

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    Fuyu-8B Model Resources

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    Fuyu-8B AI technology page Hackathon projects

    Discover innovative solutions crafted with Fuyu-8B AI technology page, developed by our community members during our engaging hackathons.

    Data Tonic

    Data Tonic

    Enterprise Autonomation Agent Do not wait for accounting, legal or business intelligence reporting with uncertain quality and long review cycles. DataTonic accelerates the slowest part of analysis : data processing and project planning execution. Main Benefits DataTonic is unique for many reasons : local and secure application threads. compatible with microsoft enterprise environments. based on a rigorous and reproducible evaluation method. developper friendly : easily plug in new functionality and integrations. How we use it : Multi-Consult Technology You can use datatonic however you want, here's how we're using it : add case books to your folder for embedding : now DataTonic always presents its results in a case study! add medical textbooks to your folder for embedding : now DataTonic helps you through med-school ! add entire company business information : Data tonic is now your strategic advisor ! ask data tonic to create targetted sales strategies : now DataTonic is your sales assistant ! Data Tonic is the first multi-nested agent-builder-of-agents! Data Tonic uses a novel combination of three orchestration libraries. Each library creates it's own multi-agent environment. Each of these environments includes a code execution and code generation capability. Each of these stores data and embeddings on it's own datalake. Autogen is at the interface with the user and orchestrates the semantic kernel hub as well as using Taskweaver for data processing tasks. Semantic-kernel is a hub that includes internet browsing capabilities and is specifically designed to use taskweaver for data storage and retrieval and produce fixed intelligence assets also specifically designed for Autogen. Taskweaver is used as a plugin in semantic kernel for data storage and retrieval and also in autogen, but remains an autonomous task that can execute complex tasks in its multi-environment execution system.

    SPROUT

    SPROUT

    In the realm of agriculture, timely and accurate information can be the difference between a bountiful harvest and a failed crop. SPROUT addresses this critical need by offering an innovative platform that combines the power of AI with cutting-edge technologies like NDVI image analysis, multimodal data synthesis, and retrieval-augmented generation (RAG) to deliver real-time insights into crop health and disease diagnostics. Our target audience includes farmers, agronomists, and agricultural enterprises seeking to leverage technology for enhanced decision-making. By utilizing tools such as Vertex AI for disease classification and vector search, LangChain with LlamaIndex for nuanced query responses, and Multimodal RAG for image analysis, SPROUT offers a comprehensive solution that goes beyond traditional farming applications. One of SPROUT's unique features is the incorporation of CLIP, Hugging face Embeddings and Fuyu-8b models, which empower the platform with exceptional understanding and analysis of both textual and visual data. Our evaluation with TrueLlama and TrueChain ensures that the responses and solutions provided are not only accurate but also constantly improving. In an industry where precision and efficiency are paramount, SPROUT stands out by offering a seamless and intuitive interface through Streamlit, ensuring that our sophisticated technology translates into tangible benefits for users across the globe. With SPROUT, farmers can optimize their practices, reduce environmental impact, and secure their crops' health and productivity, ushering in a new era of sustainable and informed agriculture.

    Tru Era Applied

    Tru Era Applied

    Hackathon Submission: Enhanced Multimodal AI Performance Project Title: Optimizing Multimodal AI for Real-World Applications Overview: Our project focused on optimizing multimodal AI performance using the TruEra Machine Learning Ops platform. We evaluated 18 models across vision, audio, and text domains, employing innovative prompting strategies, performance metrics, and sequential configurations. Methodology: Prompting Strategies: Tailored prompts to maximize model response accuracy. Performance Metrics: Assessed models on accuracy, speed, and error rate. Sequential Configurations: Tested various model combinations for task-specific effectiveness. Key Models Evaluated: Vision: GPT4V, LLava-1.5, Qwen-VL, Clip (Google/Vertex), Fuyu-8B. Audio: Seamless 1.0 & 2.0, Qwen Audio, Whisper2 & Whisper3, Seamless on device, GoogleAUDIOMODEL. Text: StableMed, MistralMed, Qwen On Device, GPT, Mistral Endpoint, Intel Neural Chat, BERT (Google/Vertex). Results: Top Performers: Qwen-VL in vision, Seamless 2.0 in audio, and MistralMed in text. Insights: Balance between performance and cost is crucial. Some models like GPT and Intel Neural Chat underperformed or were cost-prohibitive. Future Directions: Focus on fine-tuning models like BERT using Vertex. Develop more connectors for TruLens for diverse endpoints. Submission Contents: GitHub Repository: [Link] Demo: [Link] Presentation: [Link] Our submission showcases the potential of multimodal AI evaluation using TruEra / TruLens in enhancing real-world application performance, marking a step forward in human-centered AI solutions.