Instructions to use mbzuai-ugrip-statement-tuning/multi_MBERT_2e-06_16_0.1_0.015_50k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mbzuai-ugrip-statement-tuning/multi_MBERT_2e-06_16_0.1_0.015_50k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mbzuai-ugrip-statement-tuning/multi_MBERT_2e-06_16_0.1_0.015_50k")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mbzuai-ugrip-statement-tuning/multi_MBERT_2e-06_16_0.1_0.015_50k") model = AutoModelForSequenceClassification.from_pretrained("mbzuai-ugrip-statement-tuning/multi_MBERT_2e-06_16_0.1_0.015_50k", device_map="auto") - Notebooks
- Google Colab
- Kaggle