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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 912f57d2efb1c67c02a2b2c459497d39aa0f1a41d4b38a32371a60b7f85009fd
- Size of remote file:
- 1.01 GB
- SHA256:
- d1c38b8a625d770e00645d02a6af4c78f0e785adccc737783ce13b0402a63598
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.