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???? Gorilla: Giant Language Mannequin Related with Large APIs

???? Gorilla: Giant Language Mannequin Related with Large APIs

2023-06-14 16:53:28


Gorilla LLM logo

Gorilla is a LLM that may present acceptable API calls.
It’s educated on three large machine studying hub datasets: Torch Hub, TensorFlow Hub and HuggingFace.
We’re quickly including new domains, together with Kubernetes, GCP, AWS, OpenAPI, and extra.
Zero-shot Gorilla outperforms GPT-4, Chat-GPT and Claude.
Gorilla is extraordinarily dependable, and considerably reduces hallucination errors.

???? Try Gorilla in 60s! No sign-ups, no installs, simply colab!
???? With Apache 2.0 licensed LLM fashions, you should use Gorilla comercially with none obligations!
???? We’re excited to listen to your suggestions and we welcome API contributions as we construct this open-source undertaking.
Be a part of us on Discord or be at liberty to e mail us!

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Giant Language Fashions (LLMs) have seen a powerful wave of advances lately,
with fashions now excelling in a wide range of duties, comparable to mathematical reasoning and program synthesis.
Nevertheless, their potential to successfully use instruments through API calls stays unfulfilled.
This can be a difficult job even for right this moment’s state-of-the-art LLMs comparable to GPT-4,
largely on account of their incapability to generate correct enter arguments and their tendency to hallucinate the incorrect utilization of an API name.
We launch Gorilla, a finetuned LLaMA-based mannequin that surpasses the efficiency of GPT-4 on writing API calls.
When mixed with a doc retriever, Gorilla demonstrates a robust functionality to adapt to test-time doc modifications, enabling versatile API updates and model modifications.
Gorilla additionally considerably mitigates the problem of hallucination, generally encountered when prompting LLMs instantly.
To guage the mannequin’s means, we introduce APIBench, a complete dataset consisting of HuggingFace, TorchHub, and TensorHub APIs.
The profitable integration of the retrieval system with Gorilla demonstrates the potential for LLMs to make use of instruments extra precisely, sustain with incessantly up to date documentation,
and consequently enhance the reliability and applicability of their outputs.
Gorilla fashions and code can be found at

See Also


Gorilla LLM logo

Instance API calls generated by GPT-4, Claude, and Gorilla for the
given immediate. On this instance, GPT-4 presents a mannequin that doesn’t exist, and Claude
picks an incorrect library. In distinction, our mannequin, Gorilla, can establish the duty accurately
and counsel a fully-qualified API name.


  title={Gorilla: Giant Language Mannequin Related with Large APIs},
  writer={Shishir G. Patil and Tianjun Zhang and Xin Wang and Joseph E. Gonzalez},
  journal={arXiv preprint arXiv:2305.15334},

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