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 tf_model.h5 from ydshieh/tiny-random-DebertaForMaskedLM: direct link, hf CLI and curl.
- Browser
- Download file 661 kB
-
https://huggingface.co/ydshieh/tiny-random-DebertaForMaskedLM/resolve/main/tf_model.h5
- Command line
-
hf download hf://ydshieh/tiny-random-DebertaForMaskedLM/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/ydshieh/tiny-random-DebertaForMaskedLM/resolve/main/tf_model.h5
661 kB
- Xet hash:
- 0423e5daeaeb8c6b50d8686d882560f3a03abc7641fef4a7aaa6a05c7fb6b570
- Size of remote file:
- 661 kB
- SHA256:
- eb7346f5fa46e2ae7a107b62ba569b3331f5aec1e7264064e5eccb6132800db6
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