Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use pabagcha/roberta_crypto_profiling_task1_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pabagcha/roberta_crypto_profiling_task1_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pabagcha/roberta_crypto_profiling_task1_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pabagcha/roberta_crypto_profiling_task1_2") model = AutoModelForSequenceClassification.from_pretrained("pabagcha/roberta_crypto_profiling_task1_2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5f31f5050f484b69275c2eb6b960ea8f37fe51a3c180cbe8889c9345e41b6264
- Size of remote file:
- 1.42 GB
- SHA256:
- f5a2f7ecfde972f755f52df95b5da2239658a137163a75ceb665757ae47b2ea4
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