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:
- 494eab2ac3f70e759cc782b11cc0b9c8450d70e843f0bace992e3c68fd4d39f1
- Size of remote file:
- 667 MB
- SHA256:
- 13a3e282065d5c33c854a859851f8172e0eb10f5792f908ed8f8b9cfd03566fc
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