TII UAE Falcon AI technology Top Builders

Explore the top contributors showcasing the highest number of TII UAE Falcon AI technology app submissions within our community.

Falcon LLM Models

Built on top of the RefinedWeb dataset and trained on several languages, Falcon is one of the best open-source models currently available. It features an architecture optimized for inference, incorporating FlashAttention and multiquery techniques.

Use Cases

Falcon can be used for a wide range of NLP tasks, including:

  • Text generation
  • Summarization
  • Translation
  • Question-answering
  • Sentiment analysis
  • Named entity recognition

You can fine-tune Falcon on your specific task and dataset to achieve better performance and adapt it to your needs.

Key Features

  • High-performance: Falcon LLMs are designed for efficient inference and provide state-of-the-art results on various NLP tasks.
  • Multilingual: Falcon models are trained on multiple languages, including English, German, Spanish, and French, with limited capabilities in other languages such as Italian, Portuguese, and Dutch.
  • Flexible: Falcon can be used for various tasks, such as text generation, summarization, translation, and question-answering, and can be fine-tuned for specific use cases.
  • Open-source: Falcon models are available under a license that allows commercial use, making them accessible for a wide range of applications.

Getting Started

To use the Falcon model, you need to have the transformers library installed. You can install it using pip:

pip install transformers

You can then use the Falcon model in your Python code as follows:

from transformers import AutoTokenizer, AutoModelForCausalLM
import transformers
import torch

model = "tiiuae/falcon-40b"

tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
sequences = pipeline(
   "Girafatron is obsessed with giraffes, the most glorious animal on the face of this Earth. Girafatron believes all other animals are irrelevant when compared to the glorious majesty of the giraffe.\nDaniel: Hello, Girafatron!\nGirafatron:",
for seq in sequences:
    print(f"Result: {seq['generated_text']}")


TII UAE Falcon AI technology Hackathon projects

Discover innovative solutions crafted with TII UAE Falcon AI technology, developed by our community members during our engaging hackathons.

News-video generation

News-video generation

The code aims to solve the challenge of generating attention-grabbing headlines for news videos by harnessing the power of natural language processing and the Falcon-40b language model. Crafting compelling news headlines is essential for engaging viewers and conveying the essence of a news story effectively. However, manually creating these headlines can be time-consuming and creatively demanding. This solution automates the headline generation process, making it more efficient and potentially improving the quality of headlines. Falcon-Generated Headlines: The system generates attention-grabbing headlines using Falcon, a cutting-edge language model. These headlines are tailored to the news topic, ensuring relevance and viewer interest. Video Frame Generation: Python's MoviePy library is employed to transform these headlines into dynamic video frames. This step enhances the visual appeal of the news video while maintaining concise and informative content. Background Music Integration: To further captivate the audience, background music is seamlessly integrated into the video. The choice of music complements the news content, enhancing emotional resonance and viewer engagement. Efficiency and Speed: By automating headline generation and video frame creation, this solution significantly reduces the time and effort required for news video production. News agencies can produce content faster and stay ahead of breaking news. Increased Engagement: Short, visually appealing news videos with relevant headlines are more likely to grab viewers' attention. This leads to higher engagement, increased views, and improved viewer retention, driving growth for news agencies.

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.