Instructions to use Tommert25/multibert2809_flow with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tommert25/multibert2809_flow with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Tommert25/multibert2809_flow")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Tommert25/multibert2809_flow") model = AutoModelForTokenClassification.from_pretrained("Tommert25/multibert2809_flow", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2c18d7ce7b6e04e4d110aedd907900e2f66ed92a7b259e8c760f41c9e7a83ce0
- Size of remote file:
- 4.03 kB
- SHA256:
- b2f1c142c47661962561089f1c38b5165451f2e30ed399ffb89874e1f4545dd2
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