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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 761109ad8f4c895983298f4033160bf338839f38bf29cf5c33778e636118438b
- Size of remote file:
- 33.2 MB
- SHA256:
- 0591dead2ecafebc89e384a0bfcc5a91afae1d68996c8364c434ecfcd414f527
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