Instructions to use benjamin/zett-hypernetwork-xlm-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use benjamin/zett-hypernetwork-xlm-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="benjamin/zett-hypernetwork-xlm-roberta-base", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("benjamin/zett-hypernetwork-xlm-roberta-base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from benjamin/zett-hypernetwork-xlm-roberta-base: direct link, hf CLI and curl.
- Browser
- Download file 18.1 MB
-
https://huggingface.co/benjamin/zett-hypernetwork-xlm-roberta-base/resolve/main/tokenizer.json
- Command line
-
hf download hf://benjamin/zett-hypernetwork-xlm-roberta-base/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/benjamin/zett-hypernetwork-xlm-roberta-base/resolve/main/tokenizer.json
18.1 MB
- Xet hash:
- 4657eba4644f64ec4a9f322f3f3d848cba4f57047849a17a4b6b0bf58024908c
- Size of remote file:
- 18.1 MB
- SHA256:
- 7c0bf0e5864f20edd35ac3f84004a2d4cd403c8a6c7fa9be6c3f76543b8bf556
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