Instructions to use Thesis-Nuuday/roberta_finetuned_nuuday_1Example with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Thesis-Nuuday/roberta_finetuned_nuuday_1Example with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Thesis-Nuuday/roberta_finetuned_nuuday_1Example")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Thesis-Nuuday/roberta_finetuned_nuuday_1Example") model = AutoModelForSequenceClassification.from_pretrained("Thesis-Nuuday/roberta_finetuned_nuuday_1Example", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Thesis-Nuuday/roberta_finetuned_nuuday_1Example: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/Thesis-Nuuday/roberta_finetuned_nuuday_1Example/resolve/main/training_args.bin
- Command line
-
hf download hf://Thesis-Nuuday/roberta_finetuned_nuuday_1Example/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/Thesis-Nuuday/roberta_finetuned_nuuday_1Example/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 021628ec57f8382da971525ec8cb0c8f441b51b56d79435e5a46f6633b00eb67
- Size of remote file:
- 4.92 kB
- SHA256:
- 89c7c27d6fa6b388ff8fe8162850d3068530e3f0ca2975c5a76b07d0bae23cd6
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