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_800.pt from dilip025/dummy-model: direct link, hf CLI and curl.
- Browser
- Download file 2.26 GB
-
https://huggingface.co/dilip025/dummy-model/resolve/9eef9c4b217f58bd15a9486f3a85d518636d74dc/satori_tienie_checkpoints/step_lightning_800.pt
- Command line
-
hf download hf://dilip025/dummy-model@9eef9c4b217f58bd15a9486f3a85d518636d74dc/satori_tienie_checkpoints/step_lightning_800.pt
-
curl -L -o step_lightning_800.pt https://huggingface.co/dilip025/dummy-model/resolve/9eef9c4b217f58bd15a9486f3a85d518636d74dc/satori_tienie_checkpoints/step_lightning_800.pt
2.26 GB
- Xet hash:
- cd3be51f8baf47b6c3a6f71f88a9d36b729c02888c0493106552dfd9d7078068
- Size of remote file:
- 2.26 GB
- SHA256:
- 312f5ec11d3e03826cebaaf6060e6b19843408c4646d75f904023926285a0717
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.