Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use vishalk4u/liar_binaryclassifier_bert_cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vishalk4u/liar_binaryclassifier_bert_cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vishalk4u/liar_binaryclassifier_bert_cased")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vishalk4u/liar_binaryclassifier_bert_cased") model = AutoModelForSequenceClassification.from_pretrained("vishalk4u/liar_binaryclassifier_bert_cased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- df87353c765d0834f101fe99c156c0a503a47743bcf9345a0c187ac7f49b9c0e
- Size of remote file:
- 4.98 kB
- SHA256:
- ff250f701fed5966270fa5a5d0c679a40ecaa2f6dacc3a28f5b4f0c72a5d6d61
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