Instructions to use adity12345/roberta-classifier_batch32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adity12345/roberta-classifier_batch32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="adity12345/roberta-classifier_batch32")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("adity12345/roberta-classifier_batch32") model = AutoModelForSequenceClassification.from_pretrained("adity12345/roberta-classifier_batch32", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from adity12345/roberta-classifier_batch32: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/adity12345/roberta-classifier_batch32/resolve/main/training_args.bin
- Command line
-
hf download hf://adity12345/roberta-classifier_batch32/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/adity12345/roberta-classifier_batch32/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 23bf3cdf388e28b67f08825682778ed13f67812e691f24e01963eb4726fe9a06
- Size of remote file:
- 5.3 kB
- SHA256:
- d57379df36eaf57d37b947c927cbea038ef334e49c4b1eff62d7b9a3bbd615b9
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