Q: Who is the crowd providing input?

Our global crowd spans 100+ countries with 40+ languages Our skilled annotators have diverse backgrounds with expertise in a wide range of fields Select annotators for your project by country, language, skill, and expertise Learn more about the Toloka crowd

Question 1

What is a Large Language Model (LLM)?

Accepted Answer

Large Language Models (LLMs) are machine learning models that understand natural language and generate human language using deep neural networks. They are pre-trained on massive text datasets, such as books, articles, and web pages, which means they perform well with general-purpose output. But they can also be fine-tuned to handle specific tasks and domains that involve language understanding, like translation, question answering, writing stories, or chatbot development.

Question 2

How does Toloka simplify working with large language models?

Accepted Answer

Models like GPT-3 are popular for natural language processing tasks. However, many businesses lack the resources and expertise to work with them. Toloka automates model fine-tuning, evaluation, and monitoring — so you can get your AI application up and running without hiring a team of experts.

Question 3

What if I need a large language model that works in a language other than English?

Accepted Answer

Large language models (LLM) that have been pre-trained with English data can be fine-tuned with data in a new language. The amount of language data required for fine-tuning is far less than the huge training dataset used for the initial training process of a large language model.Our huge global crowd can generate high-quality training data in every major world language.

Question 4

How can I make sure that LLM output is safe?

Accepted Answer

The best way to ensure that your language model is safe for users is to use human evaluation to detect any potential bias in the output. You can also use a combination of natural language processing (NLP) techniques and human moderation to detect any offensive content in the output of large language models.Toloka can help you set up an efficient moderation pipeline to make sure that your large language model output conforms to your corporate policies.

Question 5

Who is the crowd providing input?

Accepted Answer

Our global crowd spans 100+ countries with 40+ languagesOur skilled annotators have diverse backgrounds with expertise in a wide range of fieldsSelect annotators for your project by country, language, skill, and expertiseLearn more about the Toloka crowd

Question 6

Why do popular large language models need human assistance?

Accepted Answer

Large language models require a large amount of data to train, and the data needs to be labeled accurately for the language model to make accurate predictions. Humans can provide more accurate and nuanced labeling than machines. Without enough diverse data, language models can become biased or inaccurate. Human labeling can help guarantee that the data is balanced and representative of real-world use cases. Large language models are also prone to hallucinations, or inventing output that isn&#x27;t based on facts. Human evaluation of model output is essential for aligning the model with expectations.

Question 7

What about pricing?

Accepted Answer

Pricing of particular human tasks for LLM development depends on many factors, including the purpose of the model. Please contact our LLM experts to get a quote.

Question 8

Is my data private or will it be reused?

Accepted Answer

Your data that is used in any tasks related to LLM development is private and belongs to you. It will not be reused for training other models, or for any other purposes.

Question 9

Do you have hosting options?

Accepted Answer

It is assumed that the model hosting is on the client side and Toloka provides human input for its development.

Question 10

How can Toloka help with large language model development?

Accepted Answer

Large language models work well for generalized tasks because they are pre-trained on huge amounts of unlabeled text data, like textbooks, dumps of social media posts, or massive datasets of legal documents. But to get good at a specific task, language models need fine-tuning and human feedback. If you are developing your own LLM, you need high-quality labeled data.Toloka provides human-labeled data for your language model development process. We offer custom solutions for:

Dataset collection and cleaning for the initial training stage
Labeling training data to fine-tune the language model
Model tuning (creating prompts and instructions; moderating, categorizing, validating, or responding to prompts)
Reinforcement learning from human feedback (RLHF) workflows
Evaluating quality of model output
Moderating model output

Data labeling for
Generative AI and LLM

Align your model with human preferences

Get human input at all stages of LLM development

Powering new language models and research

How to make language models work for you

Chatbots & AI assistants for Customer Support & Sales

Content generation

Content summarization

Content moderation

Code assistance and generation

Financial data analysis

Why Toloka

ML technologies

Diverse global crowd

Crowdsourcing technologies

Robust secure infrastructure

Your questions answered

Accelerate time-to-value for your LLM

Data labeling for Generative AI and LLM