Instructions to use admko/sembr2023-bert-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use admko/sembr2023-bert-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="admko/sembr2023-bert-small")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("admko/sembr2023-bert-small") model = AutoModelForTokenClassification.from_pretrained("admko/sembr2023-bert-small") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b17264fb3798bcd7784820dd4e22440b46e7ff9d82cde8d73adb2f42e8940fd1
- Size of remote file:
- 114 MB
- SHA256:
- 5310962eb2ff2db4ee57fc63a36e5299a8b64deb3d455e6c645e1a18c0fb9b05
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