LLaMA: Everything you want to know about Meta’s new AI model

Facebook’s Parent Company Just Released a Game-Changing AI Model — Here’s What You Need to Know!

In the tech world, people have been focusing on the language models developed and deployed by Microsoft, Google, and OpenAI for the past few weeks. However, Meta, Facebook’s parent company, has also been making significant progress in this field and is releasing a new AI language generator called LLaMA.

LLaMA differs from ChatGPT or Bard. It is not a system that anyone can talk to. Instead, it is a research tool that needs people to use Prompt engineering. LLaMA is designed to help researchers advance their work in the subfield of AI.

Model details:

The FAIR team of Meta AI developed the LLaMA model between December 2022 and February 2023. This is the first version of the model, and it is an auto-regressive language model based on the transformer architecture. The model comes in four different sizes, which are 7B, 13B, 33B, and 65B parameters.

LLaMA’s multiple sizes and diversity of data sources make it a versatile tool for researchers.

The main purposes for which LLaMA was designed are as follows:

• Investigation of possible applications, such as question answering, natural language comprehension, and reading comprehension.
• Examination of the capabilities and limitations of existing language models.
• Development of strategies to enhance language models.
• Evaluation and management of biases, risks, toxic and harmful content generation, as well as hallucinations.
• Solving complex Mathematical theorems
• Predicting new Protein structures

Meta is explicitly calling out that LLaMA is designed as a foundational model and is not intended for downstream applications without additional risk assessment and mitigation. It has not been trained with human feedback and therefore may generate harmful or unhelpful content and misinformation.

LLaMA Outperforms GPT-3 and Competes with Top Models

LLaMA model, as reported by the FAIR team, surpasses GPT-3 and is on par with other leading models. LLaMA is a collection of language models with different sizes, ranging from 7 billion to 65 billion parameters. These models were trained on large amounts of publicly available data, containing trillions of text samples.

LLaMA-13B Outperforms GPT-3 on Most Benchmarks

According to the FAIR team, LLaMA-13B, which is one of the models in the collection, performed better than GPT-3 (175B) in most tests or evaluations despite being more than 10× smaller. Another model in the collection LLaMA-65B was found to be comparable to some of the best-performing models such as Chinchilla70B and PaLM-540B.

Diversity of Data Sources Used to Train LLaMA

LLaMA was trained in 20 different languages, but due to the majority of the training data being English, it’s expected to perform better in English than in other languages. The FAIR team also found that the model’s performance may vary for different dialects.

The FAIR team trained the model using different sources of data, such as CCNet, C4, GitHub, Wikipedia, books, ArXiv, and Stack Exchange. The majority of the data came from CCNet, which made up 67% of the total data used.

Bias Evaluation Results of the LLaMA Model

In order to evaluate the model’s biases, the FAIR team used RAI datasets to measure its exhibition of biases towards gender, religion, race, sexual orientation, age, nationality, disability, physical appearance, and socio-economic status. They also measured the toxicity of the model’s generations depending on the context used to prompt it.

The results show that the LLaMA model has an average bias score of 66.6 across all categories, with lower scores indicating lower bias. It is important to note that the bias score varies for each category. The FAIR team found that the model had the lowest bias score of 57 for race/color and the highest bias score of 81 for sexual orientation.

LLaMA’s bias evaluation results show the importance of continuous monitoring and management of AI models.

How to Apply for access to LLaMA:

Access to the model will be granted selectively to academic researchers, individuals associated with the government, civil society and academia, and industry research facilities across the globe. General users will not have access to the model at this time. However, if you meet the criteria outlined above, you can fill out the form provided and await further information regarding access.

https://docs.google.com/forms/d/e/1FAIpQLSfqNECQnMkycAp2jP4Z9TFX0cGR4uf7b_fBxjY_OjhJILlKGA/viewform

Meta believes that the release of these models to the research community could help accelerate the development of large language models and improve their robustness and mitigate known issues like toxicity and bias.