Instructions to use funnel-transformer/medium-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use funnel-transformer/medium-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="funnel-transformer/medium-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("funnel-transformer/medium-base") model = AutoModel.from_pretrained("funnel-transformer/medium-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ecdf40fe55b4d1bfd307fed4658d50579f6561cf4684170436d823a20dd34814
- Size of remote file:
- 462 MB
- SHA256:
- 68572d3313626c24d086fbb6d85ef4c07ccc1cb8fc2aabac806a02f6704c7610
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