Instructions to use syssec-utd/py314-pylingual-v5-mlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use syssec-utd/py314-pylingual-v5-mlm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="syssec-utd/py314-pylingual-v5-mlm")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("syssec-utd/py314-pylingual-v5-mlm") model = AutoModelForMaskedLM.from_pretrained("syssec-utd/py314-pylingual-v5-mlm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0771b4da6ed54a4771845d0f8c08704f45601245755c03dd19975001b6c58081
- Size of remote file:
- 5.27 kB
- SHA256:
- bbfedd7ce849b7b325d792f55fc7f094ec04fe03cfb1459bedd3f2c29980b7b8
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