Instructions to use funnel-transformer/intermediate-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use funnel-transformer/intermediate-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="funnel-transformer/intermediate-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("funnel-transformer/intermediate-base") model = AutoModel.from_pretrained("funnel-transformer/intermediate-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from funnel-transformer/intermediate-base: direct link, hf CLI and curl.
- Browser
- Download file 647 MB
-
https://huggingface.co/funnel-transformer/intermediate-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://funnel-transformer/intermediate-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/funnel-transformer/intermediate-base/resolve/main/pytorch_model.bin
647 MB
- Xet hash:
- 116ff9095e5b1f0c26c200a91cbde6f27e84b7ed57ac06b60ed8393b96a87dec
- Size of remote file:
- 647 MB
- SHA256:
- 521e57784f7e38bca6dad3368695b8abe5d3ecf1e52cb75efcad15ecb4e9ad53
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