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:
- 6e2aea5deac29249ba8723f9d180e3ee2789f0921df1ab2dfcd2f2bda463dc78
- Size of remote file:
- 627 Bytes
- SHA256:
- d6909a416a7bf2940518cb42f3a0c6246bfa0515d91f83c593494c7aae53171c
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