Instructions to use Drigoro/roberta_mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Drigoro/roberta_mini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Drigoro/roberta_mini")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Drigoro/roberta_mini") model = AutoModelForSequenceClassification.from_pretrained("Drigoro/roberta_mini", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Drigoro/roberta_mini: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/Drigoro/roberta_mini/resolve/main/training_args.bin
- Command line
-
hf download hf://Drigoro/roberta_mini/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Drigoro/roberta_mini/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- e54e2f05dd232abae6ee58418dcc985842e696b0c4179e0d585052db2187e0c0
- Size of remote file:
- 5.11 kB
- SHA256:
- 11be26193d8cfc95d40356c418cbc750ddee50cd2b6d78adc8d2c6cae545fc58
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