Instructions to use GRMenon/dp-roberta-large-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GRMenon/dp-roberta-large-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="GRMenon/dp-roberta-large-finetuned")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("GRMenon/dp-roberta-large-finetuned") model = AutoModelForSequenceClassification.from_pretrained("GRMenon/dp-roberta-large-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from GRMenon/dp-roberta-large-finetuned: direct link, hf CLI and curl.
- Browser
- Download file 4.35 kB
-
https://huggingface.co/GRMenon/dp-roberta-large-finetuned/resolve/main/training_args.bin
- Command line
-
hf download hf://GRMenon/dp-roberta-large-finetuned/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/GRMenon/dp-roberta-large-finetuned/resolve/main/training_args.bin
4.35 kB
- Xet hash:
- 26efb1b85a0d3c7e27d4bc74d6c755bcf045a292c0a75a11d920523662811d17
- Size of remote file:
- 4.35 kB
- SHA256:
- 27acbe67982ef0db2715fbd2c4682f50faeca0dc99400cb6e9eb7dfec2607ec3
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