Instructions to use VCNC/bert_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VCNC/bert_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="VCNC/bert_3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("VCNC/bert_3") model = AutoModelForSequenceClassification.from_pretrained("VCNC/bert_3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6efdbf600af68fd6ec6afc1d7a845f25ad4fbd8700dbea069965dc7b2c3fa1b4
- Size of remote file:
- 346 MB
- SHA256:
- aaaabb8c5675ad01ffa990d8601d834361f04be0c788fe218a59456fb1ab688e
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