Instructions to use kontur-ai/sbert_punc_case_ru with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kontur-ai/sbert_punc_case_ru with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="kontur-ai/sbert_punc_case_ru")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("kontur-ai/sbert_punc_case_ru") model = AutoModelForTokenClassification.from_pretrained("kontur-ai/sbert_punc_case_ru", device_map="auto") - Notebooks
- Google Colab
- Kaggle
remove auth token requirement
Browse files
sbert_punc_case_ru/sbertpunccase.py
CHANGED
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@@ -77,13 +77,8 @@ class SbertPuncCase(nn.Module):
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super().__init__()
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self.tokenizer = AutoTokenizer.from_pretrained(MODEL_REPO,
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revision="sbert",
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use_auth_token=True,
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strip_accents=False)
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self.model = AutoModelForTokenClassification.from_pretrained(MODEL_REPO
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revision="sbert",
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use_auth_token=True
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)
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self.model.eval()
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def forward(self, input_ids, attention_mask):
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super().__init__()
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self.tokenizer = AutoTokenizer.from_pretrained(MODEL_REPO,
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strip_accents=False)
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self.model = AutoModelForTokenClassification.from_pretrained(MODEL_REPO)
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self.model.eval()
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def forward(self, input_ids, attention_mask):
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