Instructions to use muhtasham/tiny-mlm-glue-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use muhtasham/tiny-mlm-glue-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="muhtasham/tiny-mlm-glue-mrpc")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("muhtasham/tiny-mlm-glue-mrpc") model = AutoModelForMaskedLM.from_pretrained("muhtasham/tiny-mlm-glue-mrpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 532df724b86b54da63ea714a835b80582d4b6162a1f4d3ac9566049f9ee7d03f
- Size of remote file:
- 3.52 kB
- SHA256:
- ffe3172c693fd088c95f55e3cb6fd2c4cab4aafd3d50382266c04d5ecd393718
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