Text Classification
Transformers
PyTorch
TensorBoard
data2vec-text
Generated from Trainer
Eval Results (legacy)
Instructions to use mrm8488/data2vec-text-base-finetuned-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/data2vec-text-base-finetuned-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mrm8488/data2vec-text-base-finetuned-mrpc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mrm8488/data2vec-text-base-finetuned-mrpc") model = AutoModelForSequenceClassification.from_pretrained("mrm8488/data2vec-text-base-finetuned-mrpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3e6d0414f607c2c50a8839210423a28f08751211f2b957bac81f23558e0ed0dc
- Size of remote file:
- 3.12 kB
- SHA256:
- 0465f7d7a2eefb71d54a7afad4cf38ccbb5b315980befeae5faa9b650b6e1b12
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