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Sing Au strati a Grand T our of the UK Eng land, Ireland, Scotland & Wales 21st July 8th August 2019 Booking Form Title: Sex: Group: First Name (as in passport): Middle Name (as in passport): Family
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01
Go to the huggingface.co website
02
Click on the 'Sign In' button located on the top right corner of the homepage
03
If you already have an account, enter your email and password to login. If not, click on the 'Sign Up' button and follow the instructions to create a new account
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Once you have successfully logged in, navigate to the 'Dashboard' section
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In the dashboard, you will find various options and functionalities. To fill out huggingface.co, click on the 'Upload a model' or 'Add a dataset' buttons, depending on what you want to contribute
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Follow the prompts and guidelines provided to complete the required information for the model or dataset you are adding. This may include details such as name, description, tags, license, etc.
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Once you have filled out all the necessary information, click on the 'Submit' button to upload your model or dataset
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Wait for the submission to be reviewed and approved by the huggingface.co team
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Hugging Face (huggingface.co) is a platform that caters to a wide range of individuals and organizations, including:
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- Natural Language Processing (NLP) researchers and practitioners who need access to state-of-the-art NLP models and tools
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- Data scientists and machine learning engineers who want to leverage pre-trained models and datasets for their NLP tasks
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- Companies and organizations that need NLP solutions for various use cases, such as text classification, sentiment analysis, question answering, etc.
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Hugging Face is a company specializing in natural language processing technologies and offers an open-source platform for machine learning models, particularly focused on transformers.
Individuals and organizations that utilize Hugging Face's model sharing, model hosting services, or participate in their community-driven projects may be required to file, depending on their specific use and contributions.
To fill out the necessary forms for Hugging Face, users should provide detailed information about their project, models, contributions, and any relevant datasets or publications linked with their work on the platform.
The purpose of Hugging Face is to democratize machine learning by providing accessible tools and a collaborative platform for developers and researchers to create, share, and improve machine learning models.
Users must report information regarding their model's architecture, training data, performance metrics, and any specific licensing or usage guidelines they intend to implement.
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