Instructions to use vumichien/sequence-classification-bigbird-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vumichien/sequence-classification-bigbird-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vumichien/sequence-classification-bigbird-roberta-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vumichien/sequence-classification-bigbird-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("vumichien/sequence-classification-bigbird-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from vumichien/sequence-classification-bigbird-roberta-base: direct link, hf CLI and curl.
- Browser
- Download file 512 MB
-
https://huggingface.co/vumichien/sequence-classification-bigbird-roberta-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://vumichien/sequence-classification-bigbird-roberta-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/vumichien/sequence-classification-bigbird-roberta-base/resolve/main/pytorch_model.bin
512 MB
- Xet hash:
- 2848dfbaa6949ddbb607e805a3320b2ac54465647e3683c806d406df2e3294a9
- Size of remote file:
- 512 MB
- SHA256:
- 82d8c3fb2ed9597b6f9e6e9ee9b17a30099979d86488890a043a9781c5f08759
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