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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
5951e9d
1
Parent(s): 6be9e9a
Upload config.json with huggingface_hub
Browse files- config.json +2 -2
config.json
CHANGED
|
@@ -1,5 +1,5 @@
|
|
| 1 |
{
|
| 2 |
-
"_name_or_path": "
|
| 3 |
"activation_dropout": 0.0,
|
| 4 |
"adapter_attn_dim": null,
|
| 5 |
"adapter_kernel_size": 3,
|
|
@@ -110,7 +110,7 @@
|
|
| 110 |
1
|
| 111 |
],
|
| 112 |
"torch_dtype": "float32",
|
| 113 |
-
"transformers_version": "4.
|
| 114 |
"use_weighted_layer_sum": false,
|
| 115 |
"vocab_size": 3086,
|
| 116 |
"xvector_output_dim": 512
|
|
|
|
| 1 |
{
|
| 2 |
+
"_name_or_path": "/kaggle/working/speech_folder_5/checkpoint-54500",
|
| 3 |
"activation_dropout": 0.0,
|
| 4 |
"adapter_attn_dim": null,
|
| 5 |
"adapter_kernel_size": 3,
|
|
|
|
| 110 |
1
|
| 111 |
],
|
| 112 |
"torch_dtype": "float32",
|
| 113 |
+
"transformers_version": "4.30.2",
|
| 114 |
"use_weighted_layer_sum": false,
|
| 115 |
"vocab_size": 3086,
|
| 116 |
"xvector_output_dim": 512
|