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📸 𝗬𝗢𝗟𝗢𝘃𝟵: 𝗥𝗲𝗱𝗲𝗳𝗶𝗻𝗶𝗻𝗴 𝗥𝗲𝗮𝗹-𝗧𝗶𝗺𝗲 𝗢𝗯𝗷𝗲𝗰𝘁 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻 YOLOv9 takes real-time object detection to the next level, outpacing its previous versions YOLOv7 and YOLOv8 with superior accuracy, efficiency, and model compactness.  Let’s dig in why YOLOv9 is the standout evolution of the series: 💡 𝗦𝘂𝗽𝗲𝗿𝗶𝗼𝗿 𝘁𝗼 𝗬𝗢𝗟𝗢𝘃𝟳 𝗮𝗻𝗱 𝗬𝗢𝗟𝗢𝘃𝟴: YOLOv9 boasts fewer parameters than YOLOv7 and YOLOv8 while delivering higher accuracy. It maintains computational efficiency similar to YOLOv7, avoiding the extra complexity seen in YOLOv8. Outperforms even other state-of-the-art models like RT DETR and RTMDet. 💡 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗮𝗯𝗹𝗲 𝗚𝗿𝗮𝗱𝗶𝗲𝗻𝘁 𝗜𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻 (𝗣𝗚𝗜): PGI tackles information bottlenecks, enhancing gradient propagation for better model learning. The added computations are removed at inference time, ensuring no increase in inference cost. 💡𝗚𝗲𝗻𝗲𝗿𝗮𝗹𝗶𝘇𝗲𝗱 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝘁 𝗟𝗮𝘆𝗲𝗿 𝗔𝗴𝗴𝗿𝗲𝗴𝗮𝘁𝗶𝗼𝗻 𝗡𝗲𝘁𝘄𝗼𝗿𝗸 (𝗚𝗘𝗟𝗔𝗡): GELAN fuses the power of CSPNet and ELAN, optimizing both inference speed and feature extraction while remaining lightweight—perfect for real-time detection. 💡𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀: Autonomous vehicles: Detect pedestrians, vehicles, and road signs Surveillance systems: Monitor public spaces and identify suspicious activities Retail analytics: Track customer movements and analyze foot traffic 💡𝗜𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻: • Available on GitHub (WongKinYiu/yolov9) • Requires Python and PyTorch • Can be run in Docker container for easier setup 💡𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴 𝗽𝗿𝗼𝗰𝗲𝘀𝘀: • Prepare dataset in COCO format • Use train_dual.py script with specified hyperparameters • Supports multi-GPU training via torch.distributed 💡𝗘𝘃𝗮𝗹𝘂𝗮𝘁𝗶𝗼𝗻: • Utilize val.py or val_dual.py scripts to assess model performance YOLOv9 sets a new benchmark in real-time object detection, delivering unmatched accuracy and efficiency for a wide range of computer vision applications! #YOLOv9 #ObjectDetection #AI #DeepLearning #AutonomousTech #Surveillance #RetailTech #ML

📚 𝗦𝘂𝗽𝗲𝗿𝘁𝗲𝗮𝗺𝘀.𝗮𝗶 𝗗𝗶𝗴𝗲𝘀𝘁: 𝗔𝗜 𝗶𝗻 𝗥𝗲𝘁𝗮𝗶𝗹 - 𝗜𝗺𝗽𝗮𝗰𝘁 𝗮𝗻𝗱 𝗖𝗮𝘀𝗲 𝗦𝘁𝘂𝗱𝗶𝗲𝘀 🔍 In this edition: Uncover the 𝘁𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝘃𝗲 𝗽𝗼𝘄𝗲𝗿 𝗼𝗳 𝗔𝗜 𝗶𝗻 𝗿𝗲𝘁𝗮𝗶𝗹 🛒, explore the 𝗵𝗼𝘁𝘁𝗲𝘀𝘁 𝘁𝗿𝗲𝗻𝗱𝘀 𝗶𝗻 𝗚𝗲𝗻 𝗔𝗜 , dive into 𝗴𝗿𝗼𝘂𝗻𝗱𝗯𝗿𝗲𝗮𝗸𝗶𝗻𝗴 𝗔𝗜 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵 you can't afford to miss , and stay ahead with the 𝗹𝗮𝘁𝗲𝘀𝘁 𝘁𝗿𝗲𝗻𝗱𝗶𝗻𝗴 𝗯𝗹𝗼𝗴𝘀 𝗮𝗻𝗱 𝘁𝘂𝘁𝗼𝗿𝗶𝗮𝗹𝘀 . 📈 𝗧𝗼𝗽 𝗔𝗜 𝗧𝗿𝗲𝗻𝗱𝘀 𝗶𝗻 𝗥𝗲𝘁𝗮𝗶𝗹: • Multimodal AI: Enhancing retail through seamless integration of text, images, and video. • YOLOv8: Real-time object detection driving efficiency in inventory and customer behavior analysis. • Predictive Analytics: Leveraging data-driven insights for forecasting and optimization in retail. 💡 𝗟𝗮𝘁𝗲𝘀𝘁 𝗔𝗜 𝗡𝗲𝘄𝘀: • Phi-3.5-MoE: Microsoft’s newest model, boasting 42 billion parameters, excelling in multilingual support and safety. • xAI's Grok-2: Advanced image generation and top-tier chatbot performance. • NVIDIA’s Mistral-NeMo-Minitron 8B: Cutting-edge performance with optimized model pruning. 🔬 𝗡𝗲𝘄 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗦𝗽𝗼𝘁𝗹𝗶𝗴𝗵𝘁: • CogVLM2: Advanced visual-language models for enhanced image and video understanding. • NVIDIA’s LongVILA: Pushing the boundaries of video analysis with long-context visual-language models. • Meta's Hand Tracking Algorithm: Revolutionizing hand-tracking technology for complex gestures and VR. • Sapiens Model Family: Meta's foundation for human-centric vision tasks, excelling in real-world applications. 💡 𝗖𝗮𝘀𝗲 𝗦𝘁𝘂𝗱𝗶𝗲𝘀 𝗼𝗳 𝗔𝗜 𝗣𝗼𝘄𝗲𝗿𝗶𝗻𝗴 𝗥𝗲𝘁𝗮𝗶𝗹: • Unilever's BeautyHub PRO: AI-driven personalization leading to significant sales growth. • Home Depot’s SideKick App: ML-powered in-store efficiency for better product availability and task management. • Nike’s A.I.R. Project: Pioneering generative AI in product design for athletic innovation. 🔗 Get a full breakdown here: https://lnkd.in/dvZVE9QJ #AIinRetail #GenerativeAI #ArtificialIntelligence #AIResearch #TechInnovation #RetailTech #MachineLearning #DeepLearning #ComputerVision #AITrends #SupplyChainOptimization #CustomerExperience #AIinBusiness #TechNews #FutureOfRetail #SuperteamsAI

🔍 Experimenting with FLUX.1 🔍 Our team recently got hands-on with the cutting-edge FLUX.1 model by Black Forest Labs, and we’re excited to share our insights! 🚀 After diving into its capabilities, we’ve put together a detailed blog outlining our feedback and findings. We explore how FLUX.1 stands out with its innovative implementation of Flow Matching and DIT (Discrete Integrate and Transfer) architecture. 👏 A special shoutout to our developer Jayesh Gulani for publishing their first blog on Superteams.ai! 👉 Read the full blog here: https://lnkd.in/dtwpzj5z #AI #MachineLearning #DeepLearning #TechInnovation #ArtificialIntelligence #GenAI #SuperteamsAI #Flux #BlackForestLabs

🔍 𝗘𝘁𝗵𝗶𝗰𝘀 𝗮𝗻𝗱 𝗔𝗜: 𝗛𝗼𝘄 𝗼𝗳𝘁𝗲𝗻 𝗱𝗼 𝘄𝗲 𝗰𝗼𝗻𝘀𝗶𝗱𝗲𝗿 𝘁𝗵𝗲 𝗶𝗺𝗽𝗮𝗰𝘁? The conversation around ethics and AI is intensifying, especially in a world where AI is increasingly influencing content creation. At a time when AI has moved from ‘futuristic’ to ‘essential’, and we are concerned about privacy infringement, bias, and ethical implications, 𝗔𝗜 𝗴𝘂𝗮𝗿𝗱𝗿𝗮𝗶𝗹𝘀 are stepping in as an external observer, ensuring that the results received by the AI system are accurate and legit. AI guardrails for content help prevent abuse and harmful content. Guardrails ensure that AI-generated enterprise content is safe and compliant with both regulations and company standards. Dive into our latest blog on superteams.ai to explore the 𝗘𝘁𝗵𝗶𝗰𝗮𝗹 𝗟𝗮𝗻𝗱𝘀𝗰𝗮𝗽𝗲 𝗼𝗳 𝗔𝗜 𝗶𝗻 𝗖𝗼𝗻𝘁𝗲𝗻𝘁 and discover how we can navigate these challenges responsibly. 🌐 🔗 𝗥𝗲𝗮𝗱 𝘁𝗵𝗲 𝗳𝘂𝗹𝗹 𝗯𝗹𝗼𝗴 𝗵𝗲𝗿𝗲:https://lnkd.in/gtjqiqc9 #AI #EthicalAI #ContentCreation #ArtificialIntelligence #SuperteamsAI #Ethics #GenAI #ResponsibleAI #AIguardrails

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As an open-source suite of text-to-image models, 𝗙𝗹𝘂𝘅.𝟭 𝗯𝘆 Black Forest Labs, sets a new benchmark in the industry, combining state-of-the-art image synthesis with unparalleled prompt adherence, style diversity, and scene complexity.   🔍 𝗪𝗵𝘆 𝗙𝗹𝘂𝘅.𝟭 𝗦𝘁𝗮𝗻𝗱𝘀 𝗢𝘂𝘁:   • 𝗢𝗽𝗲𝗻-𝗦𝗼𝘂𝗿𝗰𝗲 𝗔𝗰𝗰𝗲𝘀𝘀: Democratizing advanced generative AI capabilities for developers and creators.   • 𝗧𝗵𝗿𝗲𝗲 𝗣𝗼𝘄𝗲𝗿𝗳𝘂𝗹 𝗩𝗮𝗿𝗶𝗮𝗻𝘁𝘀: From top-tier [Pro] performance to efficient [Dev] and lightning-fast [Schnell] models, Flux.1 offers versatility for every need.   • 𝗖𝘂𝘁𝘁𝗶𝗻𝗴-𝗘𝗱𝗴𝗲 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲: 12B parameters, hybrid multimodal transformer blocks, and flow matching for unmatched visual quality and efficiency.   Dive into the full announcement from Black Forest Labs and discover how Flux.1 is reshaping the generative AI landscape. 🌐   🔗 Explore Flux.1 and more at Black Forest Labs: https://lnkd.in/eUrSe47y At Superteams.ai, we love boundaries of innovation being pushed through open source! That’s why we’re particularly excited about the latest breakthrough from Black Forest Labs.   #GenerativeAI #OpenSource #AIInnovation #TextToImage #BlackForestLabs

🎧 𝗠𝗮𝘀𝘁𝗲𝗿𝗶𝗻𝗴 𝗔𝗜-𝗣𝗼𝘄𝗲𝗿𝗲𝗱 𝗔𝗦𝗥 𝗳𝗼𝗿 𝗕𝗙𝗦𝗜: 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗔𝗦𝗥 𝗦𝘆𝘀𝘁𝗲𝗺 𝗨𝘀𝗶𝗻𝗴 𝗪𝗮𝘃𝟮𝗩𝗲𝗰 𝟮.𝟬   In this blog, we use the open-source Wav2Vec 2.0 model to build a robust Automatic Speech Recognition (ASR) system for the Banking, Financial Services, and Insurance (BFSI) sector.   𝗪𝗵𝘆 𝗪𝗮𝘃𝟮𝗩𝗲𝗰 𝟮.𝟬?   Wav2Vec 2.0 is a state-of-the-art self-supervised learning approach developed by Facebook AI, for speech recognition that can be fine-tuned with limited amounts of transcribed data.   𝗞𝗲𝘆 𝗛𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝘀 𝗼𝗳 𝘁𝗵𝗲 𝗯𝗹𝗼𝗴:   • 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 𝗥𝗲𝗾𝘂𝗶𝗿𝗲𝗺𝗲𝗻𝘁𝘀: We outline the specific needs of the BFSI sector and how ASR can enhance customer interactions.   • 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 𝗗𝗲𝘀𝗶𝗴𝗻: A detailed look at the architecture components necessary for a robust ASR system.   • 𝗗𝗮𝘁𝗮 𝗣𝗿𝗲𝗽𝗮𝗿𝗮𝘁𝗶𝗼𝗻: Best practices for collecting and preprocessing data to train your ASR models effectively.   • 𝗠𝗼𝗱𝗲𝗹 𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴: Insights into selecting the right algorithms and training methodologies to achieve optimal performance.   • 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗲𝘀: Guidance on deploying your ASR system in a secure and scalable manner.   👉 𝗖𝗵𝗲𝗰𝗸 𝗼𝘂𝘁 𝘁𝗵𝗲 𝗳𝘂𝗹𝗹 𝗮𝗿𝘁𝗶𝗰𝗹𝗲 𝗵𝗲𝗿𝗲: https://lnkd.in/ddEzncc9 #AI #ASR #BFSI #Wav2Vec #OpenSource #ArtificialIntelligence #TechBlog #Developers #MachineLearning

Hi guys, we’re happy to release the second edition of our newsletter, where we discuss why we love open-source AI. Here’s a quick recap of the top highlights of the fortnight gone by. 𝗥𝗲𝗰𝗼𝗺𝗺𝗲𝗻𝗱𝗲𝗱 𝗔𝗜 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗣𝗮𝗽𝗲𝗿𝘀 𝘆𝗼𝘂 𝗰𝗼𝘂𝗹𝗱 𝗱𝗶𝗽 𝗶𝗻𝘁𝗼: The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery: https://lnkd.in/eGdn_b7J HybridRAG: Integrating Knowledge Graphs and Vector Retrieval Augmented Generation for Efficient Information Extraction: https://lnkd.in/ed6MU48J TOOLSANDBOX: A Stateful, Conversational, Interactive Evaluation Benchmark for LLM Tool Use Capabilities: https://lnkd.in/dm8ntdwm LM Transparency Tool: Interactive Tool for Analyzing Transformer Language Models: https://lnkd.in/dC8Pe5na 𝗦𝗻𝗲𝗮𝗸 𝗽𝗲𝗲𝗸 𝗶𝗻𝘁𝗼 𝗼𝘂𝗿 𝗟𝗮𝘁𝗲𝘀𝘁 𝗕𝗹𝗼𝗴𝘀: 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮𝗻 𝗔𝗜-𝗣𝗼𝘄𝗲𝗿𝗲𝗱 𝗔𝗦𝗥 𝗦𝘆𝘀𝘁𝗲𝗺 𝗳𝗼𝗿 𝘁𝗵𝗲 𝗕𝗙𝗦𝗜 𝗦𝗲𝗰𝘁𝗼𝗿: 𝗔 𝗦𝘁𝗲𝗽-𝗯𝘆-𝗦𝘁𝗲𝗽 𝗚𝘂𝗶𝗱𝗲 :  Learn how to use the open-source Wav2Vec 2.0 model to build a robust Automatic Speech Recognition (ASR) system for the BFSI industry:   https://lnkd.in/ddEzncc9 𝗔𝗜 𝗶𝗻 𝗥𝗲𝘁𝗮𝗶𝗹: 𝗜𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗶𝗻𝗴 𝗜𝗻-𝗦𝘁𝗼𝗿𝗲 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝘄𝗶𝘁𝗵 𝗢𝗯𝗷𝗲𝗰𝘁 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻 𝗔𝗜 :In this blog, we demonstrate how Object Detection AI model YOLOv8 (You Only Look Once), is redefining the way retailers monitor customer behavior through in-store analytics  https://lnkd.in/dSrRw5CE 𝗛𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝗶𝗻𝗴 𝘀𝗼𝗺𝗲 𝗧𝗼𝗽 𝗧𝗿𝗲𝗻𝗱𝗶𝗻𝗴 𝗕𝗹𝗼𝗴𝘀 𝗳𝗿𝗼𝗺 𝗔𝘂𝗴𝘂𝘀𝘁: 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮 𝗖𝗵𝗮𝘁𝗯𝗼𝘁 𝗳𝗼𝗿 𝗠𝗲𝗻𝘁𝗮𝗹 𝗛𝗲𝗮𝗹𝘁𝗵 𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗮𝘁𝗶𝗼𝗻𝘀 𝗨𝘀𝗶𝗻𝗴 𝗗𝗦𝗣𝘆  This blog explores how by combining DSPy and Qdrant, one can build a powerful chatbot for mental health conversations that retrieves and incorporates relevant information to generate high-quality responses. https://lnkd.in/daVYVQBp 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮 𝗩𝗶𝘀𝘂𝗮𝗹 𝗦𝗲𝗮𝗿𝗰𝗵 𝗘𝗻𝗴𝗶𝗻𝗲 𝗳𝗼𝗿 𝗘-𝗰𝗼𝗺𝗺𝗲𝗿𝗰𝗲: 𝗔 𝗚𝘂𝗶𝗱𝗲 𝗨𝘀𝗶𝗻𝗴 𝗬𝗢𝗟𝗢 𝗮𝗻𝗱 𝗜𝗻𝗱𝗲𝘅𝗶𝗳𝘆 Here, the author builds a visual search system using the YOLO (You Only Look Once) model along with Indexify. The YOLO model is fine-tuned for object detection, while Indexify is used for scalable embedding generation and extraction. https://lnkd.in/dChcbq3A You can sign up to our newsletter here: http://www.superteams.ai/ #generativeai #ai #opensourceai #aiapplications

🔎𝗥𝗲𝗮𝗹-𝗧𝗶𝗺𝗲 𝗥𝗲𝘁𝗮𝗶𝗹 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀: 𝗣𝗼𝘄𝗲𝗿 𝗼𝗳 𝗢𝗯𝗷𝗲𝗰𝘁 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻 𝗔𝗜 𝗳𝗼𝗿 𝗜𝗻-𝗦𝘁𝗼𝗿𝗲 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 In our latest blog, we show how Object Detection AI, powered by models like YOLO (You Only Look Once), is redefining the way retailers monitor customer behavior and optimize their physical spaces. 💡 𝗞𝗲𝘆 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀: •𝗥𝗲𝗮𝗹-𝗧𝗶𝗺𝗲 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝘄𝗶𝘁𝗵 𝗬𝗢𝗟𝗢𝘃𝟴: Understand how the YOLOv8 with higher recall, precision, and enhanced capacity to detect smaller objects, identifies and tracks customer interactions in real-time. •𝗘𝗻𝗵𝗮𝗻𝗰𝗲𝗱 𝗦𝘁𝗼𝗿𝗲 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲: Learn how retailers can optimize store layouts, improve product placements, and enhance customer experiences using AI-driven analytics. •𝗜𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗲𝘀: A technical walkthrough of deploying object detection AI in retail environments, from data preparation to real-world application. Read more about the technical aspects and implementation strategies here: https://lnkd.in/dSrRw5CE #InStoreAnalytics #ObjectDetectionAI #RetailTech #AIinRetail #YOLO #AI #RetailInnovation

🎯 Elevate your LLM performance with 𝗚𝗣𝗧𝗲𝗮𝗰𝗵𝗲𝗿! In our latest blog, we fine-tuned LLMs using 𝗟𝗹𝗮𝗺𝗮 𝟮, 𝗚𝗣𝗧𝗲𝗮𝗰𝗵𝗲𝗿, 𝗮𝗻𝗱 𝘁𝗵𝗲 𝗣𝗘𝗙𝗧 (𝗣𝗮𝗿𝗮𝗺𝗲𝘁𝗲𝗿 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝘁 𝗙𝗶𝗻𝗲-𝘁𝘂𝗻𝗶𝗻𝗴) 𝗺𝗼𝗱𝗲𝗹. 𝗚𝗣𝗧𝗲𝗮𝗰𝗵𝗲𝗿 is a powerful tool that utilizes a collection of modular datasets generated by GPT-4, including: • 𝗚𝗲𝗻𝗲𝗿𝗮𝗹-𝗜𝗻𝘀𝘁𝗿𝘂𝗰𝘁: For broad instructional tasks. • 𝗥𝗼𝗹𝗲𝗽𝗹𝗮𝘆-𝗜𝗻𝘀𝘁𝗿𝘂𝗰𝘁: Tailored for role-playing scenarios. • 𝗖𝗼𝗱𝗲-𝗜𝗻𝘀𝘁𝗿𝘂𝗰𝘁: Designed for coding-related instructions. • 𝗧𝗼𝗼𝗹𝗳𝗼𝗿𝗺𝗲𝗿: Optimized for tool-use cases. By leveraging these datasets, GPTeacher ensures that your models are fine-tuned with precision, optimizing them for specific use cases while maintaining efficiency. 𝗞𝗲𝘆 𝗧𝗮𝗸𝗲𝗮𝘄𝗮𝘆𝘀: • 𝗟𝗹𝗮𝗺𝗮 𝟮 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻: Enhance your LLM’s performance with this advanced model. • 𝗧𝗲𝗸𝗻𝗶𝘂𝗺 𝗚𝗣𝗧𝗲𝗮𝗰𝗵𝗲𝗿: Fine-tune using modular datasets for targeted, efficient optimization. • 𝗣𝗘𝗙𝗧 𝗠𝗼𝗱𝗲𝗹: Apply Parameter Efficient Fine-tuning to achieve high-impact results with minimal resources. Whether you're optimizing outputs or enhancing specific use cases, this guide offers a detailed breakdown of the process. Read the full blog here: https://lnkd.in/d-TsGSXB #AI #MachineLearning #LLM #Llama2 #GPTeacher #PEFT #TechInnovation