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 satori_v2/step_lightning_20500.pt from dilip025/dummy-model: direct link, hf CLI and curl.
- Browser
- Download file 4.35 GB
-
https://huggingface.co/dilip025/dummy-model/resolve/main/satori_v2/step_lightning_20500.pt
- Command line
-
hf download hf://dilip025/dummy-model/satori_v2/step_lightning_20500.pt
-
curl -L -o step_lightning_20500.pt https://huggingface.co/dilip025/dummy-model/resolve/main/satori_v2/step_lightning_20500.pt
4.35 GB
- Xet hash:
- 575e427b2fb1b773bc0e5c77a2b7fd7658bd2941f4f88610d7da624de36267f7
- Size of remote file:
- 4.35 GB
- SHA256:
- 3fa7286ffe9b32064b09898b62c6e2923778f680837311a48d096ef424980495
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