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
Upload roberta-base_wikidata_prop_label_removed_metrics.json with huggingface_hub
Browse files
roberta-base_wikidata_prop_label_removed_metrics.json
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{"accuracy": 0.8144329896907216, "precision": 0.6075134910751349, "recall": 0.5832362082362083, "f1": 0.5373336009097599}
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