Instructions to use quipohealth/Bert_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use quipohealth/Bert_Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="quipohealth/Bert_Classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("quipohealth/Bert_Classification") model = AutoModelForSequenceClassification.from_pretrained("quipohealth/Bert_Classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc57493509ceaa3950360f0fdad22b9d03a109da7bd3ebc964b84813a12cd268
- Size of remote file:
- 4.86 kB
- SHA256:
- 4f753bed43dd0ed342f244436846b69292fe3e8f17a14d876b9cb9f616bebd36
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