Instructions to use miladfa7/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use miladfa7/output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="miladfa7/output")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("miladfa7/output") model = AutoModelForMaskedLM.from_pretrained("miladfa7/output") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9fcfd3896b1fdfefef09fd25d0c56e55fbfb0b8fd045c290b347b38472ad92b2
- Size of remote file:
- 1.52 kB
- SHA256:
- fa7ad8d7b3576b695050d8b01195c1d241c1eecb3722d0fea714c846ed7afb6e
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