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:
- 9ed878f8f331ee5fd53c6ec312614246bc220b17a48b51d479eb247c51166213
- Size of remote file:
- 16 MB
- SHA256:
- 8793826fac602a3b97a8065f9c4247f05fa6ee8c8d43ea9ac5e6755f29ef14d1
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