FlauBERT is designed for specialized chatbots that require deep, nuanced language understanding and, while it demands extensive training data and computational resources, it provides unparalleled performance in complex domains.
Use Case in Chatbots:
FlauBERT is best suited for sophisticated chatbot applications that demand a high level of language understanding. This is particularly useful for customer service chatbots, or those deployed in complex domains like healthcare or legal advice.
FlauBERT, being a BERT-based model, usually requires extensive data for fine-tuning—around 100 or more samples per intent are recommended for optimal performance. The model was initially trained on a large corpus of French web data, giving it a robust understanding of the language.
Training FlauBERT can be computationally intensive and time-consuming, especially if you're fine-tuning the model for specific tasks. However, the performance gains often justify the increased training time.
Updated about 1 month ago