Automatic Speech Recognition
Transformers
PyTorch
Persian
wav2vec2
common_voice
Generated from Trainer
Instructions to use ghofrani/common6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ghofrani/common6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ghofrani/common6")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("ghofrani/common6") model = AutoModelForCTC.from_pretrained("ghofrani/common6") - Notebooks
- Google Colab
- Kaggle
update model card README.md
Browse files
README.md
CHANGED
|
@@ -1,5 +1,9 @@
|
|
| 1 |
---
|
|
|
|
|
|
|
| 2 |
tags:
|
|
|
|
|
|
|
| 3 |
- generated_from_trainer
|
| 4 |
datasets:
|
| 5 |
- common_voice
|
|
@@ -13,7 +17,7 @@ should probably proofread and complete it, then remove this comment. -->
|
|
| 13 |
|
| 14 |
# common6
|
| 15 |
|
| 16 |
-
This model is a fine-tuned version of [common6/checkpoint-3500](https://huggingface.co/common6/checkpoint-3500) on the
|
| 17 |
It achieves the following results on the evaluation set:
|
| 18 |
- Loss: 0.3706
|
| 19 |
- Wer: 0.3421
|
|
|
|
| 1 |
---
|
| 2 |
+
language:
|
| 3 |
+
- fa
|
| 4 |
tags:
|
| 5 |
+
- automatic-speech-recognition
|
| 6 |
+
- common_voice
|
| 7 |
- generated_from_trainer
|
| 8 |
datasets:
|
| 9 |
- common_voice
|
|
|
|
| 17 |
|
| 18 |
# common6
|
| 19 |
|
| 20 |
+
This model is a fine-tuned version of [common6/checkpoint-3500](https://huggingface.co/common6/checkpoint-3500) on the COMMON_VOICE - FA dataset.
|
| 21 |
It achieves the following results on the evaluation set:
|
| 22 |
- Loss: 0.3706
|
| 23 |
- Wer: 0.3421
|