Falcon LLM is a generative large language model (LLM) that helps advance applications and use cases to future-proof our world. Today the Falcon 2, 180B, 40B, 7.5B, 1.3B parameter AI models
It’s Open-Source, Multilingual, and Multimodal – and is only AI Model with Vision-to-Language Capabilities.
Falcon 2
It is Open-Source, Multilingual, and Multimodal – and is only AI Model with Vision-to-Language Capabilities. New Falcon 2 11B Outperforms Meta’s Llama 3 8B, and Performs on par with leading Google Gemma 7B Model, as Independently Verified by Hugging Face Leaderboard.
tiiuae/falcon-7b-instruct · Hugging Face
Falcon 7B
Falcon-7B is a 7B parameters causal decoder-only model built by TII and trained on 1,500B tokens of RefinedWeb enhanced with curated corpora. It is made available under the Apache 2.0 license.
tiiuae/falcon-7b-instruct · Hugging Face
Nextgen Falcon 2 LLM is two ground-breaking versions.
Falcon 2 11B- a more efficient and accessible LLM trained on 5.5 trillion tokens
Falcon 2 11B VLM – distinguished by its vision-to-language model (VLM) capabilities.
Falcon 2 11B VLM – it enables the seamless conversion of visual inputs into textual outputs. While both models are multilingual, notably, Falcon 2 11B VLM stands out as TII’s first multimodal model – and the only one currently in the top tier market that has this image-to-text conversion capability, marking a significant advancement in AI innovation.
Falcon 40B
Falcon 40B was the world’s top-ranked open-source AI model when launched. Falcon has 40 billion parameters and was trained on one trillion tokens. For two months following its launch, Falcon 40B ranked #1 on Hugging Face’s leaderboard for open source large language models (LLMs). Offered completely royalty-free with weights, Falcon 40B is revolutionary and helps democratize AI and make it a more inclusive technology.
The multilingual Falcon 40B LLM works well with English, German, Spanish, French, Italian, Portuguese, Polish, Dutch, Romanian, Czech, and Swedish languages. The foundational LLM serves as a versatile base model that can be fine-tuned for specific requirements or objectives.
Falcon 40B launched a Call for Proposals from scientists, researchers, and innovators for inspiring use cases and applications with the most exceptional use cases to receive an investment of training computing power to work on the powerful model to shape transformative solutions. The model uses only 75 percent of GPT-3’s training compute, 40 percent of Chinchilla AI’s, and 80 percent of PaLM-62B’s.
One of the core differences in the development of Falcon was the quality of the training data. The size of the pre-training data collected for Falcon 40B was nearly five trillion tokens gathered from public web crawls (~80%), research papers, legal text, news, literature, and social media conversations.
Since LLMs are particularly sensitive to the data they are trained on, team built a custom data pipeline to extract high-quality pre-training data using extensive filtering and deduplication, implemented both at the sample level and at the string level.
tiiuae/falcon-40b · Hugging Face
Falcon 180B
Falcon 180B is a super-powerful language model with 180 billion parameters, trained on 3.5 trillion tokens. It’s currently at the top of the Hugging Face Leaderboard for pre-trained Open Large Language Models and is available for both research and commercial use..
This model performs exceptionally well in various tasks like reasoning, coding, proficiency, and knowledge tests, even beating competitors like Meta’s LLaMA 2.
Among closed source models, it ranks just behind OpenAI’s GPT 4, and performs on par with Google’s PaLM 2 Large, which powers Bard, despite being half the size of the model.
tiiuae/falcon-180B · Hugging Face
Falcon Demo -Try out Falcon on this demo platform!