初始化项目，由ModelHub XC社区提供模型

Model: ayoubkirouane/whisper-small-ar
Source: Original Platform

README.md

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+---
+language:
+- ar
+license: apache-2.0
+base_model: openai/whisper-small
+datasets:
+- mozilla-foundation/common_voice_11_0
+model-index:
+- name: Whisper-small-ar
+  results: []
+library_name: transformers
+pipeline_tag: automatic-speech-recognition
+---
+
+# Arabic-Whisper Small
+
+## Description
+
+Whisper-small-ar is an Automatic Speech Recognition (ASR) model fine-tuned specifically for the Arabic language using the Whisper model architecture. ASR models are designed to convert spoken language into written text. This model has been fine-tuned on the Mozilla Common Voice dataset (version 11.0) to transcribe spoken Arabic speech into textual form.
+
+### Key Features
+
+- **Arabic Language Support:** Whisper-small-ar is optimized for recognizing and transcribing the Arabic language accurately. It can handle various Arabic dialects and accents.
+
+- **Transformer Architecture:** The model is built on a powerful Transformer-based encoder-decoder architecture, which has demonstrated state-of-the-art performance in various natural language processing tasks, including ASR.
+
+- **Fine-tuned for Arabic ASR:** The model has undergone a fine-tuning process on a substantial amount of Arabic speech data, making it well-suited for a wide range of ASR applications in Arabic, such as transcription of podcasts, call center recordings, and more.
+
+- **Open-Source:** Whisper-small-ar is open-source and available for use by the research and developer community, facilitating the advancement of ASR technology for the Arabic language.
+
+- **Compatible with Hugging Face Transformers:** You can easily integrate and utilize this model in your ASR projects using the Hugging Face Transformers library.
+
+### Use Cases
+
+Whisper-small-ar can be employed in a variety of ASR use cases, including:
+
+- **Transcription Services:** Convert spoken Arabic content, such as audio recordings, podcasts, or videos, into written text for indexing, search, or translation purposes.
+
+- **Voice Assistants:** Enhance voice-activated systems and virtual assistants with accurate Arabic speech recognition capabilities.
+
+- **Language Processing Applications:** Integrate the model into applications involving Arabic language processing, such as sentiment analysis, keyword extraction, and more.
+
+- **Multilingual ASR:** Combine Whisper-small-ar with other multilingual ASR models for applications requiring recognition of multiple languages.
+
+## Usage
+```python
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+
+pipe = pipeline("automatic-speech-recognition", model="ayoubkirouane/whisper-small-ar")
+
+def transcribe(audio):
+    text = pipe(audio)["text"]
+    return text
+```