Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use ymlee/finetuned-bert-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ymlee/finetuned-bert-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ymlee/finetuned-bert-mrpc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ymlee/finetuned-bert-mrpc") model = AutoModelForSequenceClassification.from_pretrained("ymlee/finetuned-bert-mrpc") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ef6d06c1888e98ff2f6eceb162d13001968d77b56a1573464d4daf870e000646
- Size of remote file:
- 5.05 kB
- SHA256:
- cfd6394f30104d8891c9acfaffe4217e153b9912d026b2f16d23d67d357477de
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.