Instructions to use VCNC/bert_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VCNC/bert_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="VCNC/bert_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("VCNC/bert_2") model = AutoModelForSequenceClassification.from_pretrained("VCNC/bert_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8c9787db61be70d854d00938069d901521b6b5e01d5db7b6255f83d31f7112e8
- Size of remote file:
- 627 Bytes
- SHA256:
- 83e9efe3690ff9a3fa0833a1fd6e3d3a2ee753521e1cd9c6c3596bdf6991ad17
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