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/main/pytorch_model.bin
- Command line
-
hf download hf://ydshieh/tiny-random-DebertaForMaskedLM/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ydshieh/tiny-random-DebertaForMaskedLM/resolve/main/pytorch_model.bin
370 kB
- Xet hash:
- 27016047c35f0e4ca38451dac8d0ab0e58d18754acd50beb6a438bc8f7e26ba5
- Size of remote file:
- 370 kB
- SHA256:
- 7246944c5dd4a0c45ea3ce779bb77910d8f3d20df6baf9ab27401ed504c7a6d5
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