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Add the whisper small model. (#490)
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@ -243,10 +243,15 @@ pub fn token_id(tokenizer: &Tokenizer, token: &str) -> candle::Result<u32> {
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#[derive(Clone, Copy, Debug, ValueEnum)]
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enum WhichModel {
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Tiny,
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#[value(name = "tiny.en")]
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TinyEn,
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Base,
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#[value(name = "base.en")]
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BaseEn,
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Small,
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#[value(name = "small.en")]
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SmallEn,
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#[value(name = "medium.en")]
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MediumEn,
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LargeV2,
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}
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@ -254,7 +259,7 @@ enum WhichModel {
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impl WhichModel {
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fn is_multilingual(&self) -> bool {
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match self {
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Self::Tiny | Self::Base | Self::LargeV2 => true,
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Self::Tiny | Self::Base | Self::Small | Self::LargeV2 => true,
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Self::TinyEn | Self::BaseEn | Self::SmallEn | Self::MediumEn => false,
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}
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}
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@ -264,6 +269,7 @@ impl WhichModel {
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Self::TinyEn => ("openai/whisper-tiny.en", "refs/pr/15"),
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Self::Base => ("openai/whisper-base", "refs/pr/22"),
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Self::BaseEn => ("openai/whisper-base.en", "refs/pr/13"),
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Self::Small => ("openai/whisper-small", "main"),
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Self::SmallEn => ("openai/whisper-small.en", "refs/pr/10"),
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Self::MediumEn => ("openai/whisper-medium.en", "refs/pr/11"),
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Self::LargeV2 => ("openai/whisper-large-v2", "refs/pr/57"),
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@ -287,7 +293,7 @@ struct Args {
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revision: Option<String>,
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/// The model to be used, can be tiny, small, medium.
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#[arg(long, default_value = "tiny-en")]
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#[arg(long, default_value = "tiny.en")]
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model: WhichModel,
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/// The input to be processed, in wav format, will default to `jfk.wav`. Alternatively
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