Instructions to use moussaKam/frugalscore_small_deberta_bert-score with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moussaKam/frugalscore_small_deberta_bert-score with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="moussaKam/frugalscore_small_deberta_bert-score")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("moussaKam/frugalscore_small_deberta_bert-score") model = AutoModelForSequenceClassification.from_pretrained("moussaKam/frugalscore_small_deberta_bert-score", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from moussaKam/frugalscore_small_deberta_bert-score: direct link, hf CLI and curl.
- Browser
- Download file 2.54 kB
-
https://huggingface.co/moussaKam/frugalscore_small_deberta_bert-score/resolve/main/training_args.bin
- Command line
-
hf download hf://moussaKam/frugalscore_small_deberta_bert-score/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/moussaKam/frugalscore_small_deberta_bert-score/resolve/main/training_args.bin
2.54 kB
- Xet hash:
- f513652cbf0c80dc71cd9706a608a89401ba0e350a574c127387f7aab033f680
- Size of remote file:
- 2.54 kB
- SHA256:
- 1c22d16a5647e0e91cba13456d06c26782bde2845bc631f8dc36ee998436bd40
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