Instructions to use nxtcoder36/dummy-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nxtcoder36/dummy-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nxtcoder36/dummy-model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nxtcoder36/dummy-model") model = AutoModelForMaskedLM.from_pretrained("nxtcoder36/dummy-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7d15bfc2643a39bcaec673c6a8d7de91bc2f981f036d84b24e91abfcd5b826d6
- Size of remote file:
- 443 MB
- SHA256:
- c4835be054b6d3ca451fac1b4a57a906e869c6f48fd101887f94fe8aa805f339
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