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:
- 1a6d8e8e7ca4b2fefd99d3bad6bdd675c03a2fac73da861508b2ad7a0d0864c3
- Size of remote file:
- 17.7 MB
- SHA256:
- 491c4ceb8a88645c29fa0faa4533c8466b6c23bde1155b6f7053dbc52f94053a
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