Aya Expanse-8b

A multilingual large language model supporting 23 languages

CommonProductProgrammingMultilingualText Generation

Aya Expanse is an open-weight research model with advanced multilingual capabilities. It merges high-performance pre-trained models with one year of research from Cohere For AI, including data arbitrage, multilingual preference training, safety tuning, and model fusion. This powerful multilingual large language model serves 23 languages, including Arabic, Chinese (Simplified and Traditional), Czech, Dutch, English, French, German, Greek, Hebrew, Hindi, Indonesian, Italian, Japanese, Korean, Persian, Polish, Portuguese, Romanian, Russian, Spanish, Turkish, Ukrainian, and Vietnamese.

Text generation supporting 23 different languages
Autoregressive language modeling using an optimized transformer architecture
Supervised fine-tuning
preference training
and model fusion post-training
Operational with 8K context length
Available for trial on Hugging Face Space without the need to download weights
Provides detailed installation and usage guidelines for quick developer onboarding
Supports installation of the transformers library via pip and loading the model using AutoTokenizer and AutoModelForCausalLM
Offers a wealth of community-contributed example notebooks showcasing model applications across different use cases

\The target audience includes researchers
developers
and enterprises that require multilingual text generation. The model's support for multiple languages makes it particularly suitable for international companies needing to handle multilingual text data
as well as academic institutions conducting cross-lingual research.\

In a multilingual writing assistant
Aya Expanse can help users compose texts in different languages.
In a multilingual question-answer system
Aya Expanse can understand and respond to questions posed in various languages.
In a cooking application

1. Install the transformers library: Run `pip install 'git+https://github.com/huggingface/transformers.git'` in your terminal or command prompt.
2. Import the necessary modules: In your Python code
import AutoTokenizer and AutoModelForCausalLM.
3. Load the model and tokenizer: Use the model ID 'CohereForAI/aya-expanse-8b' to load the model and tokenizer.
4. Prepare the input data: Format the user's message into a structure that the model can accept.

Visit

Aya Expanse-8b Visit Over Time

Monthly Visits

20899836

Bounce Rate

46.04%

Page per Visit

5.2

Visit Duration

00:04:57

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Aya Expanse-8b

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