Instructions to use shamz15531/roberta_tuple_matcher_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shamz15531/roberta_tuple_matcher_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="shamz15531/roberta_tuple_matcher_base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("shamz15531/roberta_tuple_matcher_base") model = AutoModelForSequenceClassification.from_pretrained("shamz15531/roberta_tuple_matcher_base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f737da9b3b06c7fc39dc3c6e2a35e5bf91fd63de6f28c6f1ffb2fb3ca94dc954
- Size of remote file:
- 499 MB
- SHA256:
- ae74be164e3b5e9537db7b5cd3fa411afcd6592f22da17733285690d22b2ba27
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