Instructions to use RogerKam/subTopics-bigBird-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RogerKam/subTopics-bigBird-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RogerKam/subTopics-bigBird-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RogerKam/subTopics-bigBird-base") model = AutoModelForSequenceClassification.from_pretrained("RogerKam/subTopics-bigBird-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from RogerKam/subTopics-bigBird-base: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/RogerKam/subTopics-bigBird-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://RogerKam/subTopics-bigBird-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/RogerKam/subTopics-bigBird-base/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- cc9df16adb301f527fb57778489564395cf918fa8099d5c3a1707c502439e2e8
- Size of remote file:
- 499 MB
- SHA256:
- 9a14f3aadee5974357f4face057fc7d835c00966e0dd51926c1ceea792cfb3b8
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