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")# pip install -U transformers accelerate # 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
Download tokenizer.json from dilip025/dummy-model: direct link, hf CLI and curl.
- Browser
- Download file 2.42 MB
-
https://huggingface.co/dilip025/dummy-model/resolve/52e4818f41589cf5c377841a95e630005060df84/tokenizer.json
- Command line
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hf download hf://dilip025/dummy-model@52e4818f41589cf5c377841a95e630005060df84/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/dilip025/dummy-model/resolve/52e4818f41589cf5c377841a95e630005060df84/tokenizer.json
2.42 MB
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