Everyone is very familiar with the current hype around Large Language Models (LLM) such as GPT-3 and Image Generation models such as DALL-E 2 and Stable diffusion. However, the results of these models come at a price.

• GPT-3: ~$12 Million
• DALL-E: ~$500k- $1 million
• Stable Diffusion: ~$600k

This is due to the large number of GPU’s required to process and train these models. Besides the cost, the amount of labelled data required to achieve these results is difficult to source. Previously it was not possible for startups to train models of this calibre because of these two factors until now— introducing Sentence Transformer Fine-tuning (SetFit) a simple and efficient alternative for few-shot text classification unveiled by the teams at Intel Labs, UKP Labs and Hugging Face. Read More

#nlp