Instructions to use simecek/results2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simecek/results2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="simecek/results2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("simecek/results2") model = AutoModelForMaskedLM.from_pretrained("simecek/results2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eed5efccc4ae4aca8fd653c5bfdc48bd40e63ca84bd2746f563e68813da6e7fb
- Size of remote file:
- 5.18 kB
- SHA256:
- 9a7500ce646249e281fe640b83f55df94de3d29b8b9ff263624f6ec8d90cc481
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