Instructions to use hf-internal-testing/tiny-random-AlbertForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-AlbertForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-AlbertForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-AlbertForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-AlbertForMaskedLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 745a9d33a479396d7b1dcbbc5b3b8072d4c127c14060bea3a755165c26684976
- Size of remote file:
- 31.9 MB
- SHA256:
- d0d22f007d7b60508ad3e4341f8b33003d7ba239e11131595678b3d462878e50
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