Instructions to use ruaccent/RUAccent-stressed-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ruaccent/RUAccent-stressed-encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ruaccent/RUAccent-stressed-encoder")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ruaccent/RUAccent-stressed-encoder") model = AutoModel.from_pretrained("ruaccent/RUAccent-stressed-encoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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license: mit
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Вот карточка модели на русском языке для репозитория ruaccent/RUAccent-stressed-encoder:
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# RUAccent-stressed-encoder
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outputs = model(**inputs)
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last_hidden_state = outputs.last_hidden_state
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```
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license: mit
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language:
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- ru
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# RUAccent-stressed-encoder
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outputs = model(**inputs)
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last_hidden_state = outputs.last_hidden_state
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```
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