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
Download texts.json from dilip025/dummy-model: direct link, hf CLI and curl.
- Browser
- Download file 518 MB
-
https://huggingface.co/dilip025/dummy-model/resolve/b0cabf8afeef7eb6b72f215e699e99e655515084/texts.json
- Command line
-
hf download hf://dilip025/dummy-model@b0cabf8afeef7eb6b72f215e699e99e655515084/texts.json
-
curl -L -o texts.json https://huggingface.co/dilip025/dummy-model/resolve/b0cabf8afeef7eb6b72f215e699e99e655515084/texts.json
518 MB
- Xet hash:
- 767f543935d9b917c0e1705fe544f8a69dd63a434656b820406df55f97a4e74c
- Size of remote file:
- 518 MB
- SHA256:
- 82a568d89e765729c3defe617e625fa413788b4be843e14b05783e2bfa5dcd93
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