Instructions to use dilip025/dummy-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dilip025/dummy-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="dilip025/dummy-model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("dilip025/dummy-model") model = AutoModelForMaskedLM.from_pretrained("dilip025/dummy-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b06c8f4ee7a1f297145294bdadecde25e65d523983d1a852d82adf6ce3a18aee
- Size of remote file:
- 2.08 GB
- SHA256:
- e21496743fc625f0154a9ee12c0f8e09779d25cf3c8ce9b17e755a8044c3ac04
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