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
bert-large-uncased_wikidata_prop_outcome_prediction_v1 / events.out.tfevents.1731684846.hsuvaspc.527949.0
- Xet hash:
- e42f3d45a267de390e8955bb08f4e93ac2563180e9517fa27fb3b81513cc6d6f
- Size of remote file:
- 31.4 kB
- SHA256:
- fa17859119e409b25fb66e87ba482377f0b322f7fba7985e68f9a65ab27dad27
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