Instructions to use anhuu/argument_classification_UKP_sentence_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anhuu/argument_classification_UKP_sentence_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="anhuu/argument_classification_UKP_sentence_bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("anhuu/argument_classification_UKP_sentence_bert") model = AutoModelForSequenceClassification.from_pretrained("anhuu/argument_classification_UKP_sentence_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from anhuu/argument_classification_UKP_sentence_bert: direct link, hf CLI and curl.
- Browser
- Download file 4.47 kB
-
https://huggingface.co/anhuu/argument_classification_UKP_sentence_bert/resolve/109fa7a562f8b607ab2ea6f383fc0b01a381f1d8/training_args.bin
- Command line
-
hf download hf://anhuu/argument_classification_UKP_sentence_bert@109fa7a562f8b607ab2ea6f383fc0b01a381f1d8/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/anhuu/argument_classification_UKP_sentence_bert/resolve/109fa7a562f8b607ab2ea6f383fc0b01a381f1d8/training_args.bin
4.47 kB
- Xet hash:
- 6ee4db73469ef64dc1dad7551a84e0a1bccd3136369a8df07e12f8628ea440be
- Size of remote file:
- 4.47 kB
- SHA256:
- aaebfc95b7b8268c6396118e6178d6daf8e97d33a5ad562df830d2034779408e
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