RLHF and human feedback data for LLMs
Human feedback data to align language models, from preference and comparison data to red-teaming and domain-expert annotation, across 100+ languages.
RLHF data is the human feedback used to align a language model, such as ranking which of two responses is better. ConsultBae provides it, from preference and comparison data to red-teaming and domain-expert annotation, across 100+ languages.
- Preference, instruction, red-teaming, evaluation data
- Domain-expert annotators, not generic crowdwork
- Multilingual alignment across 100+ languages
- Human-in-the-loop throughout
What LLM data services does ConsultBae offer?
- Preference and comparison data for reward modeling
- Instruction and response data for tuning
- Red-teaming and safety data
- Evaluation datasets
- Domain-expert annotation
Why does the annotator decide the quality of an aligned model?
RLHF is only as good as the people giving feedback. On anything specialist, a crowdworker sets a low ceiling, because they cannot tell a good answer from a plausible wrong one. A domain expert raises that ceiling. We source for expertise, not just availability.
Can ConsultBae provide multilingual RLHF data?
Yes. Alignment work usually stops at English, which leaves a model unpredictable elsewhere. We provide preference and feedback data across 100+ languages.
Where is RLHF data used?
- Reward modeling
- Instruction tuning
- Safety and red-teaming
- Model evaluation
- Multilingual alignment
Related services
Tell us the model, the domain and the languages
A plan and a timeline within 24 hours.