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:
- 10a13018632ef8caaf9980fe941575b26fda4dbe035a168cb15838d577189550
- Size of remote file:
- 3.44 kB
- SHA256:
- 4698de98260416ca3fb16dadc8b6a45e51f1365af2e8db2c87a5cea1e66b1ff6
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