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 model.onnx from benjamin/wtp-bert-mini: direct link, hf CLI and curl.
- Browser
- Download file 14.8 MB
-
https://huggingface.co/benjamin/wtp-bert-mini/resolve/main/model.onnx
- Command line
-
hf download hf://benjamin/wtp-bert-mini/model.onnx
-
curl -L -o model.onnx https://huggingface.co/benjamin/wtp-bert-mini/resolve/main/model.onnx
14.8 MB
- Xet hash:
- 68c47faeea2a4db0f3575f42a640c8714a7dde876a332995ae99cbbb668da0db
- Size of remote file:
- 14.8 MB
- SHA256:
- 8f2e2ada50239bef37469e4187b209c70d141e02f193cdfb5436e2ed6070479a
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