Instructions to use harikrushna2272/bert-mrpc-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harikrushna2272/bert-mrpc-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="harikrushna2272/bert-mrpc-finetuned")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("harikrushna2272/bert-mrpc-finetuned") model = AutoModelForSequenceClassification.from_pretrained("harikrushna2272/bert-mrpc-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from harikrushna2272/bert-mrpc-finetuned: direct link, hf CLI and curl.
- Browser
- Download file 5.78 kB
-
https://huggingface.co/harikrushna2272/bert-mrpc-finetuned/resolve/main/training_args.bin
- Command line
-
hf download hf://harikrushna2272/bert-mrpc-finetuned/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/harikrushna2272/bert-mrpc-finetuned/resolve/main/training_args.bin
5.78 kB
- Xet hash:
- 6db2c72e28e144cb0567bb5bfa7eba5487c98f16474b8422dbda5995600174cc
- Size of remote file:
- 5.78 kB
- SHA256:
- 6a9b727cbed042cab8d62ed4b6808048c2494636c469f2af64727162f3f03581
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