Instructions to use xt0r3/aihype_deEmphasizingLimitations-vs-rest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xt0r3/aihype_deEmphasizingLimitations-vs-rest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xt0r3/aihype_deEmphasizingLimitations-vs-rest")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xt0r3/aihype_deEmphasizingLimitations-vs-rest") model = AutoModelForSequenceClassification.from_pretrained("xt0r3/aihype_deEmphasizingLimitations-vs-rest") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("xt0r3/aihype_deEmphasizingLimitations-vs-rest")
model = AutoModelForSequenceClassification.from_pretrained("xt0r3/aihype_deEmphasizingLimitations-vs-rest")Quick Links
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xt0r3/aihype_deEmphasizingLimitations-vs-rest")