Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Turkish
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use sgangireddy/whisper-medium-tr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sgangireddy/whisper-medium-tr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="sgangireddy/whisper-medium-tr")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("sgangireddy/whisper-medium-tr") model = AutoModelForSpeechSeq2Seq.from_pretrained("sgangireddy/whisper-medium-tr") - Notebooks
- Google Colab
- Kaggle
File size: 1,006 Bytes
6bf6614 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 | {
"_name_or_path": "openai/whisper-medium",
"activation_dropout": 0.0,
"activation_function": "gelu",
"architectures": [
"WhisperForConditionalGeneration"
],
"attention_dropout": 0.0,
"begin_suppress_tokens": [
220,
50257
],
"bos_token_id": 50257,
"d_model": 1024,
"decoder_attention_heads": 16,
"decoder_ffn_dim": 4096,
"decoder_layerdrop": 0.0,
"decoder_layers": 24,
"decoder_start_token_id": 50258,
"dropout": 0.0,
"encoder_attention_heads": 16,
"encoder_ffn_dim": 4096,
"encoder_layerdrop": 0.0,
"encoder_layers": 24,
"eos_token_id": 50257,
"forced_decoder_ids": null,
"init_std": 0.02,
"is_encoder_decoder": true,
"max_length": 448,
"max_source_positions": 1500,
"max_target_positions": 448,
"model_type": "whisper",
"num_hidden_layers": 24,
"num_mel_bins": 80,
"pad_token_id": 50257,
"scale_embedding": false,
"torch_dtype": "float32",
"transformers_version": "4.26.0.dev0",
"use_cache": true,
"vocab_size": 51865
}
|