Instructions to use adity12345/roberta-classifier_batch16_3dataset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adity12345/roberta-classifier_batch16_3dataset with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="adity12345/roberta-classifier_batch16_3dataset")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("adity12345/roberta-classifier_batch16_3dataset") model = AutoModelForSequenceClassification.from_pretrained("adity12345/roberta-classifier_batch16_3dataset", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from adity12345/roberta-classifier_batch16_3dataset: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/adity12345/roberta-classifier_batch16_3dataset/resolve/main/training_args.bin
- Command line
-
hf download hf://adity12345/roberta-classifier_batch16_3dataset/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/adity12345/roberta-classifier_batch16_3dataset/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 6983975910f5d94623c40b0bce0c5598901985632c510c771f80fa8ef2257f18
- Size of remote file:
- 5.3 kB
- SHA256:
- 98961709c0d4e59e7befa03f918de911ee18522fada4c56ead8afb167b4eb089
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