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:
- 64e409096e8d761060b5d53bb57d22a13740189934a0e6571250c9bab4fa35ff
- Size of remote file:
- 114 MB
- SHA256:
- 5ada6fe98490f8f013dcd826945d5685e34c5f69ec1025ec676ae4c7ebabeeff
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