Instructions to use beloiual/model_3_edges with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use beloiual/model_3_edges with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="beloiual/model_3_edges")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("beloiual/model_3_edges") model = AutoModelForTokenClassification.from_pretrained("beloiual/model_3_edges", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a29cdc479298a2805b53f3c2f1a77cca7184ef2e05858263747904f0bbea37df
- Size of remote file:
- 4.98 kB
- SHA256:
- 9a3b42ce1f6d2b200f5a7b7c20ed01c3f250324d3a97995f6a507df035ede00a
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