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:
- d5822ff4ca00f05aa3f723e9c6ad93244725a844e3f81c9d792dbb5fa62a2b50
- Size of remote file:
- 3.38 kB
- SHA256:
- cd6e817ba4c89a9e117d309e41d89a4d23a5482091f1724f446edba723a8f664
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