Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use vishalk4u/liar_binaryclassifier_roberta_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vishalk4u/liar_binaryclassifier_roberta_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vishalk4u/liar_binaryclassifier_roberta_base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vishalk4u/liar_binaryclassifier_roberta_base") model = AutoModelForSequenceClassification.from_pretrained("vishalk4u/liar_binaryclassifier_roberta_base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cbfdc99dae9f8cb6df2a55cc0f1c2944f234d05b216a6c8b7299036f2bd83f76
- Size of remote file:
- 499 MB
- SHA256:
- ac417e494b24619cbf6f5cab8f694f6ea9fde3bdac92fcef4f36e60b65e2b555
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