Instructions to use funnel-transformer/xlarge-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use funnel-transformer/xlarge-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="funnel-transformer/xlarge-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("funnel-transformer/xlarge-base") model = AutoModel.from_pretrained("funnel-transformer/xlarge-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Updates incorrect tokenizer configuration file (#2)
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (4c8edca38e4912e3a88a246dbbcf2f8f348cfa1f) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>f1efffa
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Migrate model card from transformers-repo
Read announcement at https://discuss.huggingface.co/t/announcement-all-model-cards-will-be-migrated-to-hf-co-model-repos/2755 Original file history: https://github.com/huggingface/transformers/commits/master/model_cards/funnel-transformer/xlarge-base/README.md5efaa39
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