Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use tarashagarwal/inductiv-binary-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tarashagarwal/inductiv-binary-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tarashagarwal/inductiv-binary-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tarashagarwal/inductiv-binary-classifier") model = AutoModelForSequenceClassification.from_pretrained("tarashagarwal/inductiv-binary-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 643246e452bbb1fd0c5bcb08576804d68cd759cb9521b9fde684c3ee2c7e5840
- Size of remote file:
- 5.65 kB
- SHA256:
- e115124fdf744bea2d9e5941b4df98ec80cf196b9fea35cdaf8091b2020a0b3e
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