Instructions to use VCNC/bert_tulsa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VCNC/bert_tulsa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="VCNC/bert_tulsa")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("VCNC/bert_tulsa") model = AutoModelForSequenceClassification.from_pretrained("VCNC/bert_tulsa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ca07d221dceda969c533c2c25ad9a42594a3dec72c7353214b6dfbd1c8b13fe8
- Size of remote file:
- 692 MB
- SHA256:
- cd59dd67bdf14055c08e5ab73d459837a68a24ccef7c511d7b6a71a1137b3941
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