Limitation
The key limitation of Falcon model is their limited language support as their proficiency is mainly in English, German, Spanish, and French. Support for other languages is less robust, limiting their global accessibility.
Falcon LLM: Comprehensive Guide
Falcon LLM is a large language model that is engineered to comprehend and generate human like text, showcasing remarkable improvements in natural language and generation capabilities. This article covers the fundamentals of Falcon LLM and demonstrates how can we perform text generation using Falcon LLM.
Table of Content
- What is Falcon LLM?
- Key Features of Falcon LLM
- Design Philosophy of Falcon LLM
- Key Model components of Falcon LLM
- Limitation
- Text Generation using Falcon 7B
Falcon LLM aims to set new benchmarks in AI’s ability to interact, reason, and assist in a variety of complex tasks, promising transformative impacts across industries and research domains.
Large Language Model (LLM) is a very huge model (in terms of parameter) that are generally based on the transformer architecture (a special type of neural network capable of parallel processing through self-attention mechanism) that are trained on massive amounts of text data which help them to understand and generate text like humans do. Some examples of the famous LLM are GPT-3, Google BART, PaLM. Though the LLM models like GPT-3, Google BART, and PaLM are available to the public for inference, how they have been trained is not documented in detail. Traditionally the open-source LLM model has always lagged behind these private/commercial LLM models in terms of performance and size. The lack of detailed documentation about the training process of successful large-scale models limits the research and progress of open-source models.
Let us get an understanding of the key components of the Falcon Model.