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 satori_tienie_checkpoints/step_lightning_400.pt from dilip025/dummy-model: direct link, hf CLI and curl.
- Browser
- Download file 2.26 GB
-
https://huggingface.co/dilip025/dummy-model/resolve/9369c64dd2bfbff4d6eebaa2af83b9cd4db452c4/satori_tienie_checkpoints/step_lightning_400.pt
- Command line
-
hf download hf://dilip025/dummy-model@9369c64dd2bfbff4d6eebaa2af83b9cd4db452c4/satori_tienie_checkpoints/step_lightning_400.pt
-
curl -L -o step_lightning_400.pt https://huggingface.co/dilip025/dummy-model/resolve/9369c64dd2bfbff4d6eebaa2af83b9cd4db452c4/satori_tienie_checkpoints/step_lightning_400.pt
2.26 GB
- Xet hash:
- c8c4f7c8d88de9ce5adb95516b08b2e61d8da92ca9266c07e9e576921a806b9c
- Size of remote file:
- 2.26 GB
- SHA256:
- 8a437d1e02d6c7845c28cc4af3a18638fe068e6d14d528c14208ab78c1a50b5e
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