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 texts.json from dilip025/dummy-model: direct link, hf CLI and curl.
- Browser
- Download file 517 MB
-
https://huggingface.co/dilip025/dummy-model/resolve/2336634a69ce3d41b12686a252cabda4883da02a/texts.json
- Command line
-
hf download hf://dilip025/dummy-model@2336634a69ce3d41b12686a252cabda4883da02a/texts.json
-
curl -L -o texts.json https://huggingface.co/dilip025/dummy-model/resolve/2336634a69ce3d41b12686a252cabda4883da02a/texts.json
517 MB
- Xet hash:
- af5b548c0c5a79bfea88e11391b1a3b4431ba043d58e6a98865bbc59c142f33a
- Size of remote file:
- 517 MB
- SHA256:
- ac26f22720ddf8bf90e2665cfe996c95a17cb3ea57411e407a5ade03a429279d
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