Toolformer: Language Models Can Teach Themselves to Use Tools
Schick et al., 2023, Toolformer (Advances in Neural Information Processing Systems 36 (NeurIPS 2023))
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4.1 Experimental Setup
- What models did Schick et al. compare to isolate the effect of tools?GPT-J (6.7B); GPT-J fine-tuned on the same CCNet subset without API calls; Toolformer; Toolformer with API calls disabled at decoding; and much larger OPT-66B and GPT-3 175B, all prompted zero-shot without task-specific examples of tool use.
- Schick et al., 2023, Toolformer (Advances in Neural Information Processing Systems 36 (NeurIPS 2023)), §4.1
Source
- Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Eric Hambro, Luke Zettlemoyer, Nicola Cancedda and Thomas Scialom. 2023. Toolformer: Language Models Can Teach Themselves to Use Tools. In Advances in Neural Information Processing Systems 36 (NeurIPS 2023). https://papers.nips.cc/paper_files/paper/2023/hash/d842425e4bf79ba039352da0f658a906-Abstract-Conference.html