Instructions to use moussaKam/frugalscore_medium_bert-base_mover-score with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moussaKam/frugalscore_medium_bert-base_mover-score with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="moussaKam/frugalscore_medium_bert-base_mover-score")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("moussaKam/frugalscore_medium_bert-base_mover-score") model = AutoModelForSequenceClassification.from_pretrained("moussaKam/frugalscore_medium_bert-base_mover-score", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from moussaKam/frugalscore_medium_bert-base_mover-score: direct link, hf CLI and curl.
- Browser
- Download file 166 MB
-
https://huggingface.co/moussaKam/frugalscore_medium_bert-base_mover-score/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://moussaKam/frugalscore_medium_bert-base_mover-score/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/moussaKam/frugalscore_medium_bert-base_mover-score/resolve/main/pytorch_model.bin
166 MB
- Xet hash:
- 53684813aaacddaa6cd67cecea323e77aa65e83b08836cc33564267d3ac8eca5
- Size of remote file:
- 166 MB
- SHA256:
- c9ccf06ed86038a8d9be5679261a9cfe5282906b64626ffaaa2adb981d2938d3
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