Instructions to use hsuvaskakoty/bert-large-uncased_wikidata_prop_outcome_prediction_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hsuvaskakoty/bert-large-uncased_wikidata_prop_outcome_prediction_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hsuvaskakoty/bert-large-uncased_wikidata_prop_outcome_prediction_v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hsuvaskakoty/bert-large-uncased_wikidata_prop_outcome_prediction_v1") model = AutoModelForSequenceClassification.from_pretrained("hsuvaskakoty/bert-large-uncased_wikidata_prop_outcome_prediction_v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 87c9d91b0920081cef0c43965bcafdcb26e2c450dc74e688d45b391c17e3938f
- Size of remote file:
- 5.18 kB
- SHA256:
- cad42373ce260a4eb3ee45b5c28e8871b0dae6f20fab2c1bf1ae51eb4017c850
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