Instructions to use research-dump/bert_base_year_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use research-dump/bert_base_year_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="research-dump/bert_base_year_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("research-dump/bert_base_year_classifier") model = AutoModelForSequenceClassification.from_pretrained("research-dump/bert_base_year_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 152b8f8ea3f67456148fc9baabb7c9ab13a0a8c199ac0ec9d8f868e37f963ee2
- Size of remote file:
- 438 MB
- SHA256:
- 453b6023c100d977fa35d8a5642994b586fb95c348667a52819b0976dbe6fb59
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