Instructions to use cruiser/bert_final_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cruiser/bert_final_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cruiser/bert_final_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cruiser/bert_final_model") model = AutoModelForSequenceClassification.from_pretrained("cruiser/bert_final_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dbce7496f650ee4a6c301f15f985aa3c1f5f5baff37de94380860c025feaabd3
- Size of remote file:
- 3.58 kB
- SHA256:
- 83e1feb7d1557bdae614dce5d0d73f61ea1a7f324ba65938210ed8fb967eff2e
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