Instructions to use research-dump/bert_base_temp_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use research-dump/bert_base_temp_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="research-dump/bert_base_temp_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("research-dump/bert_base_temp_classifier") model = AutoModelForSequenceClassification.from_pretrained("research-dump/bert_base_temp_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 791ff51cfa4ebce91269645381be6cfff0440881d2622ec6bfd8f273b5a697f8
- Size of remote file:
- 433 MB
- SHA256:
- cd04ecb1a6f8573819a1096eff7809dd8691aa73853a771a78cbf2db9054c14b
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