Instructions to use SmartPy/bert-hs-idpt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SmartPy/bert-hs-idpt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="SmartPy/bert-hs-idpt")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("SmartPy/bert-hs-idpt") model = AutoModelForMaskedLM.from_pretrained("SmartPy/bert-hs-idpt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from SmartPy/bert-hs-idpt: direct link, hf CLI and curl.
- Browser
- Download file 3.31 kB
-
https://huggingface.co/SmartPy/bert-hs-idpt/resolve/main/training_args.bin
- Command line
-
hf download hf://SmartPy/bert-hs-idpt/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/SmartPy/bert-hs-idpt/resolve/main/training_args.bin
3.31 kB
- Xet hash:
- a3e3e481ab00decc0f9cfb950d0314b090155c8730543d6c4aa1b9ab1d19b045
- Size of remote file:
- 3.31 kB
- SHA256:
- a2674638ca6745d5be660baa8463935f138fc719115a0b3a78bc3a464eb0bc66
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