Instructions to use funnel-transformer/large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use funnel-transformer/large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="funnel-transformer/large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("funnel-transformer/large") model = AutoModel.from_pretrained("funnel-transformer/large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from funnel-transformer/large: direct link, hf CLI and curl.
- Browser
- Download file 1.54 GB
-
https://huggingface.co/funnel-transformer/large/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://funnel-transformer/large/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/funnel-transformer/large/resolve/main/pytorch_model.bin
1.54 GB
- Xet hash:
- d03331e1c5e00888e8329f171e95ece647db47b056a5a88a175d438a3c3e3662
- Size of remote file:
- 1.54 GB
- SHA256:
- 2191d803f2e8e65360bdc7cd926008cd45d74baa33f104019de3cc927aaf81c8
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