Create README.md

README.md

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+---
+language:
+- en
+thumbnail: null
+pipeline_tag: automatic-speech-recognition
+tags:
+- whisper
+- pytorch
+- speechbrain
+- Transformer
+- hf-asr-leaderboard
+license: apache-2.0
+model-index:
+  - name: asr-whisper-tiny-sb
+    results:
+      - task:
+          name: Automatic Speech Recognition
+          type: automatic-speech-recognition
+        dataset:
+          name: LibriSpeech (clean)
+          type: librispeech_asr
+          config: clean
+          split: test
+          args:
+            language: en
+        metrics:
+          - name: Test WER
+            type: wer
+            value: 7.54
+      - task:
+          name: Automatic Speech Recognition
+          type: automatic-speech-recognition
+        dataset:
+          name: LibriSpeech (other)
+          type: librispeech_asr
+          config: other
+          split: test
+          args:
+            language: en
+        metrics:
+          - name: Test WER
+            type: wer
+            value: 17.15
+      - task:
+          name: Automatic Speech Recognition
+          type: automatic-speech-recognition
+        dataset:
+          name: Common Voice 11.0
+          type: mozilla-foundation/common_voice_11_0
+          config: hi
+          split: test
+          args:
+            language: hi
+        metrics:
+          - name: Test WER
+            type: wer
+            value: 141
+---
+
+<iframe src="https://ghbtns.com/github-btn.html?user=speechbrain&repo=speechbrain&type=star&count=true&size=large&v=2" frameborder="0" scrolling="0" width="170" height="30" title="GitHub"></iframe>
+<br/><br/>
+
+# whisper tiny SpeechBrain
+
+This repository provides all the necessary tools to perform automatic speech
+recognition from an end-to-end whisper model within
+SpeechBrain. For a better experience, we encourage you to learn more about
+[SpeechBrain](https://speechbrain.github.io).
+
+## Install SpeechBrain
+
+First of all, please install tranformers and SpeechBrain with the following command:
+
+```
+pip install speechbrain transformers==4.28.0
+```
+
+Please notice that we encourage you to read our tutorials and learn more about
+[SpeechBrain](https://speechbrain.github.io).
+
+### Transcribing your own audio files (in Arabic)
+
+```python
+
+from speechbrain.pretrained import WhisperASR
+
+asr_model = WhisperASR.from_hparams(source="chaanks/asr-whisper-tiny-sb", savedir="pretrained_models/asr-whisper-tiny-sb")
+asr_model.transcribe_file("speechbrain/chaanks/asr-whisper-tiny-sb/example.wav")
+
+
+```
+### Inference on GPU
+To perform inference on the GPU, add  `run_opts={"device":"cuda"}`  when calling the `from_hparams` method.
+
+### Training
+The model was trained with SpeechBrain.
+To train it from scratch follow these steps:
+1. Clone SpeechBrain:
+```bash
+git clone https://github.com/speechbrain/speechbrain/
+```
+2. Install it:
+```bash
+cd speechbrain
+pip install -r requirements.txt
+pip install -e .
+```
+
+3. Run Training:
+```bash
+cd recipes/CommonVoice/ASR/transformer/
+python train_with_whisper.py hparams/train_ar_hf_whisper.yaml --data_folder=your_data_folder
+```
+
+You can find our training results (models, logs, etc) [here](https://drive.google.com/drive/folders/10mYPYfj9NpDNAa0nO16Zd_K1bIEUOIpx?usp=share_link).
+
+### Limitations
+The SpeechBrain team does not provide any warranty on the performance achieved by this model when used on other datasets.
+
+#### Referencing SpeechBrain
+
+```
+@misc{SB2021,
+    author = {Ravanelli, Mirco and Parcollet, Titouan and Rouhe, Aku and Plantinga, Peter and Rastorgueva, Elena and Lugosch, Loren and Dawalatabad, Nauman and Ju-Chieh, Chou and Heba, Abdel and Grondin, Francois and Aris, William and Liao, Chien-Feng and Cornell, Samuele and Yeh, Sung-Lin and Na, Hwidong and Gao, Yan and Fu, Szu-Wei and Subakan, Cem and De Mori, Renato and Bengio, Yoshua },
+    title = {SpeechBrain},
+    year = {2021},
+    publisher = {GitHub},
+    journal = {GitHub repository},
+    howpublished = {\\\\url{https://github.com/speechbrain/speechbrain}},
+  }
+```
+
+#### About SpeechBrain
+SpeechBrain is an open-source and all-in-one speech toolkit. It is designed to be simple, extremely flexible, and user-friendly. Competitive or state-of-the-art performance is obtained in various domains.
+
+Website: https://speechbrain.github.io/
+
+GitHub: https://github.com/speechbrain/speechbrain