Text Classification
Transformers
PyTorch
English
bert
Generated from Trainer
text-embeddings-inference
Instructions to use henryscheible/eval_v2_mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use henryscheible/eval_v2_mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="henryscheible/eval_v2_mrpc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("henryscheible/eval_v2_mrpc") model = AutoModelForSequenceClassification.from_pretrained("henryscheible/eval_v2_mrpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e04ffce4429ba9f4f8cc57c9c6a160a390b5f90c228faf7d87df3b8f6b6a8bfc
- Size of remote file:
- 438 MB
- SHA256:
- b274880346162c391112b33376b3ecf8583125d151d400ab0e8769d0acaa0460
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