Instructions to use nikchar/ver_model_bert_3_classes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nikchar/ver_model_bert_3_classes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nikchar/ver_model_bert_3_classes")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nikchar/ver_model_bert_3_classes") model = AutoModelForSequenceClassification.from_pretrained("nikchar/ver_model_bert_3_classes", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0f9913b3c750b699e5854f08df5c7440711de2182746a047e2ba6fd9ad2d1637
- Size of remote file:
- 4.09 kB
- SHA256:
- dd8540b1d7ac273d04542d3b857b0bf5b8dfeec0249f588df52dce3a82316441
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