Instructions to use nikchar/ver_model_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nikchar/ver_model_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nikchar/ver_model_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nikchar/ver_model_bert") model = AutoModelForSequenceClassification.from_pretrained("nikchar/ver_model_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b1e038a79775c2e0f3786e3ed9b2a290791bf9dfa45809560b62af3137cea62c
- Size of remote file:
- 4.03 kB
- SHA256:
- 47b959450a392fea921c53e8d7c0ab1ec6a2d0986edc561bc2d279b74da29973
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