Instructions to use hf-internal-testing/tiny-random-Data2VecTextForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Data2VecTextForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-Data2VecTextForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-Data2VecTextForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-Data2VecTextForMaskedLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d2243e1e87b58f37304a7803c9a8c6290174ac7c40d46d465fc48bb6a4c41d58
- Size of remote file:
- 477 kB
- SHA256:
- 7223deb4cafdc4ed3913fd813bc99a931446f5d2f97c037097e7af5b508401d6
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