Meta Llama 2 AI technology Top Builders

Explore the top contributors showcasing the highest number of Meta Llama 2 AI technology app submissions within our community.

Llama 2: The Next Generation of Large Language Model

Developed by Meta and Microsoft, Llama 2, an advanced open-source large language model, stands as the successor to the previous model, Llama 1. As an expansive AI tool, it caters to the needs of developers, researchers, startups, and businesses. Released under a highly permissive community license, Llama 2 is available for both research and commercial use.

General
Release dateJuly 18, 2023
AuthorsMeta AI & Microsoft
Model sizes7B, 13B, 70B parameters
Model ArchitectureTransformer
Training data sourceMeta's extensive dataset
Supported languagesMultiple languages

Features of Llama 2

Llama 2 comes with significant improvements over Llama 1:

  1. Increased Training on Tokens: Llama 2 is trained on 40% more tokens, promising to deliver enhanced language understanding capabilities.
  2. Longer Context Length: With a longer context length of 4k tokens, Llama 2 is expected to maintain better context in prolonged conversations.
  3. Fine-Tuning for Dialogues: The versions of Llama 2 that are fine-tuned (Labelled Llama 2-Chat) are aimed at being optimized for dialogue applications using Reinforcement Learning from Human Feedback (RLHF).

Accessing and Using Llama 2

To utilize the potential of Llama 2, its code, pretrained models, and fine-tuned models can be accessed via the Huggingface.

Essential links pertaining to Llama 2:

Llama 2 Deployment

For an efficient deployment of Llama 2:

  • For the 7B models, "GPU [medium] - 1x Nvidia A10G" could be the choice.
  • For the 13B models, "GPU [xlarge] - 1x Nvidia A100" can be an option.
  • For the 70B models, "GPU [xxxlarge] - 8x Nvidia A100" might be suitable.

These deployments might be available on platforms like Microsoft Azure and Amazon Web Services (AWS).

Responsible Use of Llama 2

Although the use of Llama 2 is encouraged, it's crucial to follow the guidelines for responsible use. Red-teaming exercises might be utilized along with a transparency schematic, and responsible use guide and an acceptable use policy might also be provided to ensure secure and acceptable use of Llama 2. Participation in the Open Innovation AI Research Community and Llama Impact Challenge could be valuable for feedback and proposing improvements.

Conclusion

Llama 2, poised as the successor of the acclaimed Llama 1, signifies a new horizon in the landscape of large language models. The vast potential it holds is eagerly anticipated and it is hoped the global AI community will bring forth innovative and advantageous applications using Llama 2.


Meta Llama 2 AI technology Hackathon projects

Discover innovative solutions crafted with Meta Llama 2 AI technology, developed by our community members during our engaging hackathons.

Neurolitiks Politics with Multi-AI Integration

Neurolitiks Politics with Multi-AI Integration

NeuroLitiks is more than a digital tool; it's the future of political innovation. In today's world, city administrators are buried under immense data, desperately trying to identify the best path forward amidst a cloud of uncertainty. Enter Neurolitiks. Powered by state-of-the-art technologies like Expert.ia, OpenAI, Lang Chain, and Neo4j databases, our platform now integrates multiple machine learning models, including Llama 2 and Falcon, offering unparalleled analytics and insights. This fusion of technologies empowers us to discern vital information that might otherwise remain hidden or overwhelming. The rationale behind harnessing multiple AI systems? City management and policy-making are intricate, with countless interwoven threads. A singular analytical approach can't grasp this vastness. But our multi-AI setup, featuring Llama 2 and Falcon, can, facilitating a comprehensive, rounded understanding of city issues, allowing for pinpoint historical accuracy, real-time adaptability, and visionary future predictions. Initially targeting the health and education sectors in urban hubs—a $1.8 million slice of a more expansive $100 million market—Neurolitiks is not merely another digital system. It's a catalyst for monumental urban evolution. Our blend of superior databases and diverse AI models can process and decode complexity like no other, bestowing city leaders with the power to make data-driven, transformative decisions. Our mission goes beyond mere data interpretation; we aim to impart wisdom, transforming raw data into tangible strategies that can reshape city landscapes and improve the lives of their residents.

ELIZA EVOL INSTRUCT - Fine-Tuning

ELIZA EVOL INSTRUCT - Fine-Tuning

We attempted to instill the deterministic, rule-based reasoning found in ELIZA into a more advanced, probabilistic model like an LLM. This serves a dual purpose: To introduce a controlled variable in the form of ELIZA's deterministic logic into the more "fuzzy" neural network-based systems. To create a synthetic dataset that can be used for various Natural Language Processing (NLP) tasks, beyond fine-tuning the LLM. [ https://huggingface.co/datasets/MIND-INTERFACES/ELIZA-EVOL-INSTRUCT ] [ https://www.kaggle.com/code/wjburns/pippa-filter/ ] ELIZA Implementation: We implemented the script meticulously retaining its original transformational grammar and keyword matching techniques. Synthetic Data Generation: ELIZA then generated dialogues based on a seed dataset. These dialogues simulated both sides of a conversation and were structured to include the reasoning steps ELIZA took to arrive at its responses. Fine-tuning: This synthetic dataset was then used to fine-tune the LLM. The LLM learned not just the structure of human-like responses but also the deterministic logic that went into crafting those responses. Validation: We subjected the fine-tuned LLM to a series of tests to ensure it had successfully integrated ELIZA's deterministic logic while retaining its ability to generate human-like text. Challenges Dataset Imbalance: During the process, we encountered issues related to data imbalance. Certain ELIZA responses occurred more frequently in the synthetic dataset, risking undue bias. We managed this through rigorous data preprocessing. Complexity Management: Handling two very different types of language models—rule-based and neural network-based—posed its unique set of challenges. Significance This project offers insights into how the strength of classic models like ELIZA can be combined with modern neural network-based systems to produce a model that is both logically rigorous and contextually aware.

Business Llama

Business Llama

📣 Exciting News from Business Llama! 📈 🚀 We're thrilled to introduce "Business Llama: Optimized for Social Engagement," our latest project that's set to transform the way you approach business planning and go-to-market (GTM) strategies. 🌟 🤖 With the power of advanced, fine-tuned models, driven by the renowned Clarifai platform, we're taking your business strategies to the next level. Here's what you can expect: 🎯 Enhanced Decision-Making: Make smarter, data-driven decisions that lead to business success. 📊 Improved Business Plans: Develop robust and realistic plans backed by deep insights. 🌐 Optimized Go-to-Market Strategies: Reach your target audience more effectively than ever before. 🏆 Competitive Advantage: Stay ahead in the market by adapting quickly to changing conditions. 💰 Resource Efficiency: Maximize resource allocation and reduce costs. 🤝 Personalization: Tailor your offerings to individual customer preferences. ⚙️ Scalability: Apply successful strategies across various products and markets. 🛡️ Risk Mitigation: Identify and address potential risks proactively. 🔄 Continuous Improvement: Keep your strategies aligned with evolving market conditions. Join us on this journey to elevate your business game! 🚀 Stay tuned for updates and exciting insights. The future of business planning and GTM strategies is here, and it's more engaging than ever. 🌐💼 #BusinessLlama #SocialEngagement #DataDrivenDecisions #Clarifai #GTMStrategies