Instructions to use moussaKam/tiny_bert-base_bert-score with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moussaKam/tiny_bert-base_bert-score with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="moussaKam/tiny_bert-base_bert-score")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("moussaKam/tiny_bert-base_bert-score") model = AutoModelForSequenceClassification.from_pretrained("moussaKam/tiny_bert-base_bert-score", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from moussaKam/tiny_bert-base_bert-score: direct link, hf CLI and curl.
- Browser
- Download file 2.54 kB
-
https://huggingface.co/moussaKam/tiny_bert-base_bert-score/resolve/main/training_args.bin
- Command line
-
hf download hf://moussaKam/tiny_bert-base_bert-score/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/moussaKam/tiny_bert-base_bert-score/resolve/main/training_args.bin
2.54 kB
- Xet hash:
- d44827bd0bf6c681a0a51c7ac21da21cf836ad82fe6b575133cc3a4eb222373e
- Size of remote file:
- 2.54 kB
- SHA256:
- de8afc4d4e0c149b35266e25c644cf727fb6395869117b8429211b96653173c8
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