gorilla/README.md at main · ShishirPatil/gorilla #358
Labels
github
gh tools like cli, Actions, Issues, Pages
llm-evaluation
Evaluating Large Language Models performance and behavior through human-written evaluation sets
llm-experiments
experiments with large language models
llm-function-calling
Function Calling with Large Language Models
llm-inference-engines
Software to run inference on large language models
llm-serving-optimisations
Tips, tricks and tools to speedup inference of large language models
New-Label
Choose this option if the existing labels are insufficient to describe the content accurately
openai
OpenAI APIs, LLMs, Recipes and Evals
Papers
Research papers
🔥 Gorilla OpenFunctions is a drop-in alternative for function calling! Release Blog
🟢 Gorilla is Apache 2.0 With Gorilla being fine-tuned on MPT, and Falcon, you can use Gorilla commercially with no obligations! ⛳
🚀 Try Gorilla in 60s
💻 Use Gorilla in your CLI with pip install gorilla-cli
🗞️ Checkout our paper!
👋 Join our Discord!
Gorilla enables LLMs to use tools by invoking APIs. Given a natural language query, Gorilla comes up with the semantically- and syntactically- correct API to invoke. With Gorilla, we are the first to demonstrate how to use LLMs to invoke 1,600+ (and growing) API calls accurately while reducing hallucination. We also release APIBench, the largest collection of APIs, curated and easy to be trained on! Join us, as we try to expand the largest API store and teach LLMs how to write them! Hop on our Discord, or open a PR, or email us if you would like to have your API incorporated as well.
News
🔥 [11/16] Excited to release Gorilla OpenFunctions
💻 [06/29] Released gorilla-cli, LLMs for your CLI!
🟢 [06/06] Released Commercially usable, Apache 2.0 licensed Gorilla models
🚀 [05/30] Provided the CLI interface to chat with Gorilla!
🚀 [05/28] Released Torch Hub and TensorFlow Hub Models!
🚀 [05/27] Released the first Gorilla model! or 🤗!
🔥 [05/27] We released the APIZoo contribution guide for community API contributions!
🔥 [05/25] We release the APIBench dataset and the evaluation code of Gorilla!
Suggested labels
{ "key": "llm-function-calling", "value": "Tools and techniques for invoking APIs using Large Language Models" } { "key": "LLM-Applications", "value": "Practical applications of Large Language Models in software development and automation" }
The text was updated successfully, but these errors were encountered: