Instructions to use algomuffin/dummy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use algomuffin/dummy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="algomuffin/dummy")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("algomuffin/dummy") model = AutoModelForMaskedLM.from_pretrained("algomuffin/dummy") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 33ff50e44388cb05bbfb1c170ad1dca364a42b668350d05d9a24dd2ebd2beffb
- Size of remote file:
- 443 MB
- SHA256:
- 2bd492c564512fbdcd3088dc1965bddd776b5f2245a954900c8e8feee1e4b860
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.