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:
- 52337265c9a8430c7c837327f18e9d02a7634b1a10e8883858c5c35d8d733906
- Size of remote file:
- 654 MB
- SHA256:
- e4c242ca1a018d7ea596534a982fc9aa3e225c145db71d1c7eaf1a3066ee0000
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