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_medium_checkpoints/step_final_small_3669.pt from dilip025/dummy-model: direct link, hf CLI and curl.
- Browser
- Download file 3.57 GB
-
https://huggingface.co/dilip025/dummy-model/resolve/18c6ec1b53bb28d06b0e61efeb47b37032d2033f/satori_medium_checkpoints/step_final_small_3669.pt
- Command line
-
hf download hf://dilip025/dummy-model@18c6ec1b53bb28d06b0e61efeb47b37032d2033f/satori_medium_checkpoints/step_final_small_3669.pt
-
curl -L -o step_final_small_3669.pt https://huggingface.co/dilip025/dummy-model/resolve/18c6ec1b53bb28d06b0e61efeb47b37032d2033f/satori_medium_checkpoints/step_final_small_3669.pt
3.57 GB
- Xet hash:
- 8d1208ee87ff2d4fe68fee00f513f57af067d0bb9b7c526ac23caa02bb8dbd0e
- Size of remote file:
- 3.57 GB
- SHA256:
- 41bd6388442c3126b1bcb4a5c913fbbbb9033e89fcab6289d8c1f0911950cde3
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