pdelobelle
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Merge branch 'main' of https://huggingface.co/Tweeties/tweety-7b-dutch-v24a into main
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README.md
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library_name: transformers
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<p align="center">
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<img src="https://huggingface.co/DTAI-KULeuven/tweety-7b-dutch/resolve/main/tweety-7b-dutch.png?download=true" alt="Tweety-7b-dutch: A Dutch Large Language Model" width="20%">
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# Model Card for tweety-7b-dutch
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tweety-7b-dutch is a foundation model with a focus on the Dutch language, incorporating a [Dutch tokenizer](https://huggingface.co/yhavinga/gpt-neo-1.3B-dutch) for better understanding and generation of Dutch text. It's built on the mistral architecture, employing flash attention for efficient processing within a context window of 8192 tokens. Tweety-7b-dutch is trained on the [cleaned Dutch mC4 dataset](https://huggingface.co/datasets/yhavinga/mc4_nl_cleaned), without
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## Model Details
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Our tweety-7b-dutch model has an Apache 2.0 license, encouraging applications in research, content creation, and language analysis.
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- **Developed by:** KU Leuven
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- **Funded by:** VSC (Flemish Supercomputer Center), [Vlaams AI-onderzoeksprogramma](https://www.flandersairesearch.be/nl)
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- **Model type:** Foundation model
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- **Language(s) (NLP):** Dutch
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- **License:** Apache 2.0
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## Uses
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As a base model, tweety-7b-dutch is primed for direct applications across text generation and understanding within the Dutch language
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## Technical Specifications
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### Compute Infrastructure
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- nl
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library_name: transformers
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---
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[Pieter Delobelle](https://pieter.ai), [François Remy](https://fremycompany.com), [Miryam de Lhoneux](https://people.cs.kuleuven.be/~miryam.delhoneux/), [Thomas Demeester](https://tdmeeste.github.io)
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<p align="center">
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<img src="https://huggingface.co/DTAI-KULeuven/tweety-7b-dutch/resolve/main/tweety-7b-dutch.png?download=true" alt="Tweety-7b-dutch: A Dutch Large Language Model" width="20%">
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# Model Card for tweety-7b-dutch
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tweety-7b-dutch is a foundation model with a focus on the Dutch language, incorporating a [Dutch tokenizer](https://huggingface.co/yhavinga/gpt-neo-1.3B-dutch) for better understanding and generation of Dutch text. It's built on the mistral architecture, employing flash attention for efficient processing within a context window of 8192 tokens. Tweety-7b-dutch is trained on the [cleaned Dutch mC4 dataset](https://huggingface.co/datasets/yhavinga/mc4_nl_cleaned), without instruction finetuning.
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## Model Details
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Our tweety-7b-dutch model has an Apache 2.0 license, encouraging applications in research, content creation, and language analysis.
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- **Developed by:** KU Leuven and UGent
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- **Funded by:** KU Leuven BOF, VSC (Flemish Supercomputer Center), [Vlaams AI-onderzoeksprogramma](https://www.flandersairesearch.be/nl)
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- **Model type:** Foundation model
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- **Language(s) (NLP):** Dutch
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- **License:** Apache 2.0
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## Uses
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As a base model, tweety-7b-dutch is primed for direct applications across text generation and understanding within the Dutch language.
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## Technical Specifications
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### Compute Infrastructure
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