Instructions to use hf-internal-testing/tiny-random-DebertaV2ForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DebertaV2ForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-DebertaV2ForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-DebertaV2ForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-DebertaV2ForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 37865605ebeedd23dab82ac22df9c0c31e9325ec78221b50c41d3ee1b8c1e14d
- Size of remote file:
- 17.1 MB
- SHA256:
- 996efa0230ba2978b3dc24306cdf78584388b319ce457cc995ab8f274f370ddb
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