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:
- 8e2cae141816ff927e0aa658ebd3b01380a5a7cf98815c4c722ce5cd6a69d274
- Size of remote file:
- 114 MB
- SHA256:
- 9146b6e03931d05b7d6c04ecebc392bfe297ac58e0c5f15bc37765f459cb06db
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