Instructions to use cuadron11/modelBsc62 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cuadron11/modelBsc62 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="cuadron11/modelBsc62")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("cuadron11/modelBsc62") model = AutoModelForTokenClassification.from_pretrained("cuadron11/modelBsc62", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1f6276cc49fad56444a675ac7d90b0750a464ed9aee37d2e14439e3160708468
- Size of remote file:
- 496 MB
- SHA256:
- 8b7f0b0f795df6d6d3c2933d05ce7c4dfadb08b7f087c6f7149570a715c3a34b
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