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:
- cc300343a940ea59ed053df0e6ab6da817dfa185f10b77c25d3f89eef0d3ae6a
- Size of remote file:
- 1.74 GB
- SHA256:
- 233f7d31d7c67b482ece4a6fb6903b4f7f5b77694f7b387b12e441afdfed5088
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