Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use pabagcha/roberta_crypto_profiling_task1_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pabagcha/roberta_crypto_profiling_task1_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pabagcha/roberta_crypto_profiling_task1_3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pabagcha/roberta_crypto_profiling_task1_3") model = AutoModelForSequenceClassification.from_pretrained("pabagcha/roberta_crypto_profiling_task1_3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 95c7315b102681d802393fe96990d643ad8e023a1ac6a9db67538dc4b41070ac
- Size of remote file:
- 1.42 GB
- SHA256:
- 8f071f48fb0f113cd198aa85428a57debc9505753add21f93b2ebfdf9b6744c5
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