Instructions to use syssec-utd/py313-pylingual-v3-mlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use syssec-utd/py313-pylingual-v3-mlm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="syssec-utd/py313-pylingual-v3-mlm")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("syssec-utd/py313-pylingual-v3-mlm") model = AutoModelForMaskedLM.from_pretrained("syssec-utd/py313-pylingual-v3-mlm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f6ba407474debbae755a8460da8942db52b86fc18f8a185d40918ba6ba73924f
- Size of remote file:
- 5.27 kB
- SHA256:
- e28417918a5d51e8092071a3fb4e34c4d69ca38e4fdc2ee2e6e6fbb912d4a54f
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