Scaling Indic Pretraining: 2.8 Trillion Tokens and an Open Data Generation Pipeline
Hugging Face has announced a project focused on expanding pretraining for Indic languages. The work features a dataset of "2.8 Trillion Tokens" alongside an open data generation pipeline. Hugging Face has presented work on scaling pretraining for Indic languages.
Key Takeaways
- The effort centers on processing "2.8 Trillion Tokens" to improve language representation in AI systems.
The release also highlights an open data generation pipeline.
- Access to open tools for data creation helps researchers construct tailored training workflows for underrepresented language families.
Hugging Face is focusing on scaling pretraining methods specifically for Indic languages.
- An open data generation pipeline has been made available alongside the dataset.
- The pretraining effort incorporates "2.8 Trillion Tokens".
Hugging Face has presented work on scaling pretraining for Indic languages. The effort centers on processing "2.8 Trillion Tokens" to improve language representation in AI systems. The release also highlights an open data generation pipeline.
Access to open tools for data creation helps researchers construct tailored training workflows for underrepresented language families. Hugging Face is focusing on scaling pretraining methods specifically for Indic languages. The pretraining effort incorporates "2.8 Trillion Tokens".
For more details please read the original article at Hugging Face.
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