Foundation Model Data Collection and Data Annotation | Large Language Model(LLM) Data | SFT Data | Red Teaming Services

1. Overview - Unsupervised Learning: For the training data required in unsupervised learning, the provider delivers data collection and cleaning services for both single-modal and cross-modal data. We provide Large Language Model(LLM) Data cleaning and personnel support services based on the specific data types and characteristics of the client's domain. -SFT: the provider assists clients in generating high-quality supervised fine-tuning data for model optimization through prompts and outputs annotation. -Red teaming: the provider helps clients train and validate models through drafting various adversarial attacks, such as exploratory or potentially harmful questions. Our red team capabilities help clients identify problems in their models related to hallucinations, harmful content, false information, discrimination, language bias and etc. -RLHF: the provider assist clients in manually ranking multiple outputs generated by the SFT-trained model according to the rules provided by the client, or provide multi-factor scoring. By training annotators to align with values and utilizing a multi-person fitting approach, the quality of feedback can be improved. 2. Our Capacity -Global Resources: Global resources covering hundreds of languages worldwide -Compliance: All the Large Language Model(LLM) Data is collected with proper authorization -Quality: Multiple rounds of quality inspections ensures high quality data output -Secure Implementation: NDA is signed to gurantee secure implementation and data is