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aya-101

Multilingual generative language model

#natural language processing
#machine learning
#text generation
#multilingual
aya-101

Product Details

The Aya model is a large-scale multilingual generative language model capable of following instructions in 101 languages. The model outperforms mT0 and BLOOMZ on a variety of automatic and human evaluations, despite covering twice as many languages. The Aya model is trained using multiple datasets including xP3x, Aya dataset, Aya collection, a subset of the DataProvenance collection and ShareGPT-Command, and is released under the Apache-2.0 license to promote the development of multi-language technology.

Main Features

1
Text-to-text generation capabilities supporting 101 languages
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Excellent performance in automatic and human assessment in multiple languages
3
Use a variety of data sets for training, including xP3x, Aya data sets, etc.
4
Model parameters reach 13 billion, with powerful language understanding and generation capabilities
5
Provide detailed model cards, including model summary, instructions for use, model details, evaluation, bias risks and limitations, etc.
6
Support community research and encourage open source multi-language models
7
Code examples are provided to facilitate users to quickly start using the model for text generation tasks.

How to Use

1
1. Install the transformers library and use the pip command: pip install -q transformers
2
2. Import the AutoModelForSeq2SeqLM and AutoTokenizer classes
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3. Set the model checkpoint to 'CohereForAI/aya-101'
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4. Use AutoTokenizer to encode input text
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5. Use AutoModelForSeq2SeqLM to generate text
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6. Decode the generated text to get the final output result

Target Users

The target audience includes multilingual NLP researchers, developers and enterprises who need to process and generate text content in multiple languages. The Aya model is particularly suitable for users who need to develop and deploy NLP applications in multiple language environments due to its strong multilingual capabilities and open source license.

Examples

Translate Turkish to English and output accurate English translation.

Answer questions about linguistic diversity in India, providing detailed background information.

Generate text to demonstrate the model's application capabilities in different languages ​​and tasks.

Quick Access

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Categories

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› writing assistant
› AI model

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