Instructions to use hf-internal-testing/tiny-random-XmodForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-XmodForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-XmodForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-XmodForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-XmodForMaskedLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0b8a10b43c15a0cc26b20c90e4a540b960e448826f68414ce3c7d6f0ff10400a
- Size of remote file:
- 33.3 MB
- SHA256:
- 66b67caba8d16697e2615d9f83a98ade61ec4ce9d04cd722b5618d5e729fdabe
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