Whisper-Hindi2Hinglish-Swift

495
7
license:apache-2.0
by
Oriserve
Audio Model
OTHER
New
495 downloads
Early-stage
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Edge AI:
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Quick Summary

AI model with specialized capabilities.

Code Examples

Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Usage:text
- The model can be used with the [`pipeline`](https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.AutomaticSpeechRecognitionPipeline)
class to transcribe audios of arbitrary length:
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Input audio file pathtext
#### Using the OpenAI Whisper module

- First, install the openai-whisper library
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model
Print transcribed texttext
- Convert the huggingface checkpoint to a pytorch model

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