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:
- 9250502e9664996e0204d2d1c32ae9145fc598f2d75cb97471f8709ad2acc85b
- Size of remote file:
- 1.14 MB
- SHA256:
- c692aa232c435837a8484c79b1c47e09eb2274b06f6d4495017aaca77a4cded8
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