Instructions to use benjamin/wtp-bert-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use benjamin/wtp-bert-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="benjamin/wtp-bert-tiny")# Load model directly from transformers import AutoModelForTokenClassification model = AutoModelForTokenClassification.from_pretrained("benjamin/wtp-bert-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 631d841c00d6f56999c4b6ec48bdfa608970cb3e4565b5ba0b74fb3f427f90ac
- Size of remote file:
- 10.1 MB
- SHA256:
- ef8bcea523a62f59aebae72a8a1ba7fbf8361c7747048d97077dc1f61d54b59b
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