Instructions to use funnel-transformer/xlarge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use funnel-transformer/xlarge with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="funnel-transformer/xlarge")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("funnel-transformer/xlarge") model = AutoModel.from_pretrained("funnel-transformer/xlarge") - Notebooks
- Google Colab
- Kaggle
Update tf_model.h5
Browse files- tf_model.h5 +3 -0
tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:e00baf7dd2b4efd79f1adfc3539377c9f60db4476e26e02cdd566d884932c182
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size 1872707096
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