Instructions to use benjamin/wtp-bert-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use benjamin/wtp-bert-mini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="benjamin/wtp-bert-mini")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForTokenClassification model = AutoModelForTokenClassification.from_pretrained("benjamin/wtp-bert-mini", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from benjamin/wtp-bert-mini: direct link, hf CLI and curl.
- Browser
- Download file 29.6 MB
-
https://huggingface.co/benjamin/wtp-bert-mini/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://benjamin/wtp-bert-mini/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/benjamin/wtp-bert-mini/resolve/main/pytorch_model.bin
29.6 MB
- Xet hash:
- ddc86d7f5bfee0fce3b1397d3dca2746eed7176b2314d36a4eea2a08d076cfd9
- Size of remote file:
- 29.6 MB
- SHA256:
- 0a1d2957d9ba5813e577073ddd9260440f35e1b67fa405623e5140f711d6ab91
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