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HoloAssist
January 2024
A large-scale egocentric human interaction dataset, where two people collaboratively complete physical manipulation tasks.
Orca-2-7B
January 2024
Orca 2 is a finetuned version of LLAMA-2. It is built for research purposes only and provides a single turn response in tasks such as reasoning over user given data, reading comprehension, math problem solving and text summarization. The model…
LLF-Bench
January 2024
LLF Bench is a benchmark for evaluating learning agents that provides a diverse collection of interactive learning problems where the agent gets language feedback instead of rewards (as in RL) or action feedback (as in imitation learning).
imodelsX
November 2022
Scikit-learn friendly library to interpret, and prompt-engineer text datasets using large language models.
Phi-1
December 2023
The language model phi-1 is a Transformer with 1.3 billion parameters, specialized for basic Python coding. Its training involved a variety of data sources, including subsets of Python codes from The Stack v1.2, Q&A content from StackOverflow, competition code from…
AutoGen
September 2023
Enable Next-Gen Large Language Model Applications. AutoGen is a framework that enables the development of LLM applications using multiple agents that can converse with each other to solve tasks. AutoGen agents are customizable, conversable, and seamlessly allow human participation. They…
Orca-2-13B
January 2024
Orca 2 is a finetuned version of LLAMA-2. It is built for research purposes only and provides a single turn response in tasks such as reasoning over user given data, reading comprehension, math problem solving and text summarization. The model…
Trace
July 2024
Trace is a new AutoDiff-like tool for training AI systems end-to-end with general feedback (like numerical rewards or losses, natural language text, compiler errors, etc.). Trace generalizes the back-propagation algorithm by capturing and propagating an AI system’s execution trace. Trace…
Phi-2
December 2023
The phi-2 is a language model with 2.7 billion parameters. The phi-2 model was trained using the same data sources as phi-1, augmented with a new data source that consists of various NLP synthetic texts and filtered websites (for safety…