Instructions to use benjamin/wtp-canine-s-3l with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use benjamin/wtp-canine-s-3l with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="benjamin/wtp-canine-s-3l")# Load model directly from transformers import AutoModelForTokenClassification model = AutoModelForTokenClassification.from_pretrained("benjamin/wtp-canine-s-3l", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d36de999d499307517a55d5d026fadc1f12d267eaaf56543a3cfe58d46ec9adc
- Size of remote file:
- 1.26 GB
- SHA256:
- 269e05f150d86ab5a8f5ca2152b83727f511aab544d98642450f9a0af01686b7
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