Text Classification
Transformers
PyTorch
TensorBoard
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use pabagcha/roberta_crypto_profiling_task1_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_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_deberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pabagcha/roberta_crypto_profiling_task1_deberta") model = AutoModelForSequenceClassification.from_pretrained("pabagcha/roberta_crypto_profiling_task1_deberta") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 914c1877cdccd9097b0dfb66172ff162f8c4e5574eab57ad980adba38c2a9dd6
- Size of remote file:
- 3.96 kB
- SHA256:
- 9a8dd33300e67d8816356aa74ab56a291b373881ece6d340b6f960c155784f84
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