Update README.md

README.md

@@ -4,45 +4,39 @@ tags:
 model-index:
 - name: wav2vec2-russian
   results: []
+widget:
+- src: https://cdn-media.huggingface.co/speech_samples/common_voice_ru_18849022.mp3
+
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
 # wav2vec2-russian
+#
+---
+Загрузите аудиофайл в формате wav для распознования. Результат можно откорректировать в другой моей сети. которая исправляет ошибки, расставляет знаки припинания и исправляет цифры. https://huggingface.co/UrukHan/t5-russian-spell
 
-This model was trained from scratch on the None dataset.
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 1e-07
-- train_batch_size: 16
-- eval_batch_size: 8
-- seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 1000
-- num_epochs: 10
-- mixed_precision_training: Native AMP
-
-### Framework versions
-
-- Transformers 4.18.0
-- Pytorch 1.10.0+cu111
-- Datasets 2.0.0
-- Tokenizers 0.11.6
+#
+---
+# Запуск сети     пример в колабе https://colab.research.google.com/drive/1dVZvccYJq02hmEsapWgmuJ-pLdezFnn1?usp=sharing
+#
+```python
+from transformers import AutoModelForCTC, Wav2Vec2Processor
+model = AutoModelForCTC.from_pretrained("wav2vec2-russian-colab")
+processor = Wav2Vec2Processor.from_pretrained("wav2vec2-russian-colab")
+def map_to_result(batch):
+  with torch.no_grad():
+    input_values = torch.tensor(batch["input_values"]).unsqueeze(0) #, device="cuda"
+    logits = model(input_values).logits
+  pred_ids = torch.argmax(logits, dim=-1)
+  batch = processor.batch_decode(pred_ids)[0]
+  return batch
+ 
+ map_to_result()
+ ```
+ 
+ #
+ ---
+ # Тренировка модели с обработкой данных и созданием датасета разобрать можете в колабе:
+ # https://colab.research.google.com/drive/1zkCA2PtKxD2acqLr55USh35OomoOwOhm?usp=sharing