Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use pabagcha/roberta_crypto_profiling_task1_complete 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 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")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pabagcha/roberta_crypto_profiling_task1_complete") model = AutoModelForSequenceClassification.from_pretrained("pabagcha/roberta_crypto_profiling_task1_complete") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7d369d231a0541be1abf8a68aa9892f5aab3a6a2e354f3146591e7e1a23ec714
- Size of remote file:
- 1.42 GB
- SHA256:
- b8a2f6e66b009afb6351e6d944fabc56b449d6bb877969b73a56346ae829aa42
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