Instructions to use pabagcha/roberta_crypto_profiling_task1_complete_deberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pabagcha/roberta_crypto_profiling_task1_complete_deberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pabagcha/roberta_crypto_profiling_task1_complete_deberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pabagcha/roberta_crypto_profiling_task1_complete_deberta") model = AutoModelForSequenceClassification.from_pretrained("pabagcha/roberta_crypto_profiling_task1_complete_deberta") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 19659cf7c7275c93eba37064c6ad544bae815a73da5d2a8b50fd1073dde2eb94
- Size of remote file:
- 1.74 GB
- SHA256:
- d104ddc42090c7655e8939c54c0a456b7297e0c6b5cc2041fcc6a0aed7812152
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