Instructions to use shirzady1934/results5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shirzady1934/results5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="shirzady1934/results5")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("shirzady1934/results5") model = AutoModelForMaskedLM.from_pretrained("shirzady1934/results5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 08120f6e18c0a663858ec4a777e1d4a259a477962d3b0707c935a5e33f935ee9
- Size of remote file:
- 5.24 kB
- SHA256:
- 5551b1ec96498354baf0301f500b91563fd8ec8ee079a156f8d28cd62228984e
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