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
File size: 249 Bytes
db3d9f6 | 1 2 3 4 5 6 7 8 9 10 11 | {
"backend": "tokenizers",
"cls_token": "[CLS]",
"mask_token": "[MASK]",
"model_max_length": 1000000000000000019884624838656,
"pad_token": "[PAD]",
"sep_token": "[SEP]",
"tokenizer_class": "TokenizersBackend",
"unk_token": "[UNK]"
}
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