Instructions to use asparius/test-mlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use asparius/test-mlm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="asparius/test-mlm")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("asparius/test-mlm") model = AutoModelForMaskedLM.from_pretrained("asparius/test-mlm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4b3330b1eaa480f28fbae0d73f57c31dccd97178ef561d12e0ac6cefc5886951
- Size of remote file:
- 437 MB
- SHA256:
- b41e9a898ba3ce076ceb006078e22b6e8d086d05e66f588af8ff2f5d915ac1ad
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