Automatic Speech Recognition
Transformers
PyTorch
Arabic
wav2vec2
Arabic
MSA
Speech
Syllables
Wav2vec
ASR
Instructions to use IbrahimSalah/Arabic_speech_Syllables_recognition_Using_Wav2vec2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IbrahimSalah/Arabic_speech_Syllables_recognition_Using_Wav2vec2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="IbrahimSalah/Arabic_speech_Syllables_recognition_Using_Wav2vec2")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("IbrahimSalah/Arabic_speech_Syllables_recognition_Using_Wav2vec2") model = AutoModelForCTC.from_pretrained("IbrahimSalah/Arabic_speech_Syllables_recognition_Using_Wav2vec2") - Notebooks
- Google Colab
- Kaggle
Commit ·
935f259
1
Parent(s): c1d8399
Upload tokenizer_config.json with huggingface_hub
Browse files- tokenizer_config.json +14 -0
tokenizer_config.json
ADDED
|
@@ -0,0 +1,14 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"bos_token": null,
|
| 3 |
+
"clean_up_tokenization_spaces": true,
|
| 4 |
+
"do_lower_case": false,
|
| 5 |
+
"eos_token": null,
|
| 6 |
+
"model_max_length": 1000000000000000019884624838656,
|
| 7 |
+
"pad_token": "[PAD]",
|
| 8 |
+
"processor_class": "Wav2Vec2ProcessorWithLM",
|
| 9 |
+
"replace_word_delimiter_char": " ",
|
| 10 |
+
"target_lang": null,
|
| 11 |
+
"tokenizer_class": "Wav2Vec2CTCTokenizer",
|
| 12 |
+
"unk_token": "[UNK]",
|
| 13 |
+
"word_delimiter_token": "|"
|
| 14 |
+
}
|