Instructions to use ydshieh/tiny-random-DebertaForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ydshieh/tiny-random-DebertaForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ydshieh/tiny-random-DebertaForMaskedLM")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ydshieh/tiny-random-DebertaForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("ydshieh/tiny-random-DebertaForMaskedLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ydshieh/tiny-random-DebertaForMaskedLM: direct link, hf CLI and curl.
- Browser
- Download file 370 kB
-
https://huggingface.co/ydshieh/tiny-random-DebertaForMaskedLM/resolve/refs%2Fpr%2F2/pytorch_model.bin
- Command line
-
hf download hf://ydshieh/tiny-random-DebertaForMaskedLM@refs/pr/2/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/ydshieh/tiny-random-DebertaForMaskedLM/resolve/refs%2Fpr%2F2/pytorch_model.bin
370 kB
- Xet hash:
- ade7d74e3fb3481abb83377ae012a6b8bad5f592a553484d31b08e1aaf151774
- Size of remote file:
- 370 kB
- SHA256:
- 1c5c7dfe4968139dbcbbb8ef8d134687b5962c4f54b82d6d0253f81dd5e2979e
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