Crandi

Deu05232 Promptriever Ours V6 Datasets At Hugging Face

Leo Migdal
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deu05232 promptriever ours v6 datasets at hugging face

and get access to the augmented documentation experience 🤗 Datasets is a library for easily accessing and sharing AI datasets for Audio, Computer Vision, and Natural Language Processing (NLP) tasks. Load a dataset in a single line of code, and use our powerful data processing and streaming methods to quickly get your dataset ready for training in a deep learning model. Backed by the Apache Arrow format, process large datasets with zero-copy reads without any memory constraints for optimal speed and efficiency. We also feature a deep integration with the Hugging Face Hub, allowing you to easily load and share a dataset with the wider machine learning community. Find your dataset today on the Hugging Face Hub, and take an in-depth look inside of it with the live viewer.

Learn the basics and become familiar with loading, accessing, and processing a dataset. Start here if you are using 🤗 Datasets for the first time! The top public SQL queries from the community will appear here once available. 🤗 Datasets is a lightweight library providing two main features: 🎓 Documentation 🔎 Find a dataset in the Hub 🌟 Share a dataset on the Hub 🤗 Datasets is designed to let the community easily add and share new datasets.

🤗 Datasets has many additional interesting features: 🤗 Datasets originated from a fork of the awesome TensorFlow Datasets and the HuggingFace team want to deeply thank the TensorFlow Datasets team for building this amazing library. Official repository for the paper Promptriever: Instruction-Trained Retrievers Can Be Prompted Like Language Models. This repository contains the code and resources for Promptriever, which demonstrates that retrieval models can be controlled with prompts on a per-instance basis, similar to language models. NOTICE: the MTEB version of Promptriever is broken in v1, please use the v2 branch which will become the main branch soon. To initialize your research environment:

Run a MSMARCO experiment (DL19, DL20, Dev) with: The top public SQL queries from the community will appear here once available. arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community?

Learn more about arXivLabs. and get access to the augmented documentation experience If a dataset on the Hub is tied to a supported library, loading the dataset can be done in just a few lines. For information on accessing the dataset, you can click on the “Use this dataset” button on the dataset page to see how to do so. For example, samsum shows how to do so with datasets below. You can use the huggingface_hub library to create, delete, update and retrieve information from repos.

For example, to download the HuggingFaceH4/ultrachat_200k dataset from the command line, run See the HF CLI download documentation for more information. You can also integrate this into your own library! For example, you can quickly load a CSV dataset with a few lines using Pandas.

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