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:
- a6efc20975ee8d249729553c39e9fbb63fe75bd1c2897b8475d5bfb4d54034ae
- Size of remote file:
- 499 MB
- SHA256:
- 59239b9c5d6d007530dfad58ab7e6c16462b63aa7c1c83d9ad166cdc33c78da4
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