Instructions to use matverest/MCQA_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use matverest/MCQA_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="matverest/MCQA_test", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("matverest/MCQA_test") model = AutoModelForSequenceClassification.from_pretrained("matverest/MCQA_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 81c621d99f1f7f1ba3bf48e598b367df26941e5910eb05b9f917abef2b569a48
- Size of remote file:
- 11.4 MB
- SHA256:
- a5fb27619af977738eb66521f09b4d4f637353e376ffc780643afe3d7a645aae
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