RUAccent-encoders
Collection
An encoder models for TTS tasks • 2 items • Updated • 2
How to use ruaccent/RUAccent-encoder with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("feature-extraction", model="ruaccent/RUAccent-encoder") # Load model directly
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("ruaccent/RUAccent-encoder")
model = AutoModel.from_pretrained("ruaccent/RUAccent-encoder")# Load model directly
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("ruaccent/RUAccent-encoder")
model = AutoModel.from_pretrained("ruaccent/RUAccent-encoder")Эта модель представляет собой энкодер для TTS систем, который умеет разрешать омографию. Предназначен для интеграции в TTS системы, но лучше обратите внимание на энкодер который вогнали в стресс (как и автора RUAccent)
import torch
from transformers import AutoModel
import chartk
tokenizer = chartk.CharacterTokenizer.from_pretrained('ruaccent/RUAccent-encoder')
model = AutoModel.from_pretrained('ruaccent/RUAccent-stressed-encoder')
text = "На горе стоит замок"
inputs = tokenizer(text, return_tensors='pt', padding=True, truncation=True, max_length=512)
with torch.no_grad():
outputs = model(**inputs)
last_hidden_state = outputs.last_hidden_state
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ruaccent/RUAccent-encoder")