Instructions to use botcon/sample_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use botcon/sample_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="botcon/sample_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("botcon/sample_bert") model = AutoModelForSequenceClassification.from_pretrained("botcon/sample_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c8a96bcba230f0622b053ae8c57286f6728fc12495e1f638cb3c2d7ea1add983
- Size of remote file:
- 438 MB
- SHA256:
- 77100bf968d2a9dab9621feca1b8af7fbf6b273eb590dd1485e187c7d07aa5a0
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