Instructions to use syssec-utd/py314-pylingual-v7-mlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use syssec-utd/py314-pylingual-v7-mlm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="syssec-utd/py314-pylingual-v7-mlm")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("syssec-utd/py314-pylingual-v7-mlm") model = AutoModelForMaskedLM.from_pretrained("syssec-utd/py314-pylingual-v7-mlm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2cac641fa28f5687336da019684f340ff9cefb13adb54ec2edf004c0f5f210c6
- Size of remote file:
- 5.27 kB
- SHA256:
- 39776762ffdc4d1433ccb7c1464fa1050fd6a3e144e400eb1b31f619b549c6dd
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