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_prajna_checkpoints/step_lightning_24000.pt from dilip025/dummy-model: direct link, hf CLI and curl.
- Browser
- Download file 2.81 GB
-
https://huggingface.co/dilip025/dummy-model/resolve/dc909ebddd67a26f54c3d4e7df9ccca246dfc687/satori_prajna_checkpoints/step_lightning_24000.pt
- Command line
-
hf download hf://dilip025/dummy-model@dc909ebddd67a26f54c3d4e7df9ccca246dfc687/satori_prajna_checkpoints/step_lightning_24000.pt
-
curl -L -o step_lightning_24000.pt https://huggingface.co/dilip025/dummy-model/resolve/dc909ebddd67a26f54c3d4e7df9ccca246dfc687/satori_prajna_checkpoints/step_lightning_24000.pt
2.81 GB
- Xet hash:
- 67fb38528e640a92800f34762ce6d453ca21d46724445cd065e0c58c01a92543
- Size of remote file:
- 2.81 GB
- SHA256:
- f709d1db8b4ffa9600b16ff311156479701b5f0e8e828a0cf513775d226892bd
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