Instructions to use funnel-transformer/medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use funnel-transformer/medium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="funnel-transformer/medium")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("funnel-transformer/medium") model = AutoModel.from_pretrained("funnel-transformer/medium") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a086388f6afdad685801b9702d37ecb2c69cb87a4965fcaa8f69ace53ffca515
- Size of remote file:
- 524 MB
- SHA256:
- a4e61f043431a23b43be045d2e03abb8b9eb582ee699cba1275b8b8ed185a684
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.