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whisper : minor fixes (ggml-org#1154)
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README.md

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@@ -61,7 +61,7 @@ Or you can even run it straight in the browser: [talk.wasm](examples/talk.wasm)
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- Various other examples are available in the [examples](examples) folder
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The tensor operators are optimized heavily for Apple silicon CPUs. Depending on the computation size, Arm Neon SIMD
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instrisics or CBLAS Accelerate framework routines are used. The latter are especially effective for bigger sizes since
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intrinsics or CBLAS Accelerate framework routines are used. The latter are especially effective for bigger sizes since
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the Accelerate framework utilizes the special-purpose AMX coprocessor available in modern Apple products.
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## Quick start

whisper.cpp

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@@ -82,7 +82,7 @@ static void byteswap_tensor(ggml_tensor * tensor) {
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} while (0)
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#define BYTESWAP_TENSOR(t) \
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do { \
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byteswap_tensor(tensor); \
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byteswap_tensor(t); \
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} while (0)
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#else
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#define BYTESWAP_VALUE(d) do {} while (0)
@@ -589,7 +589,7 @@ struct whisper_model {
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struct whisper_sequence {
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std::vector<whisper_token_data> tokens;
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// the accumulated transcription in the current interation (used to truncate the tokens array)
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// the accumulated transcription in the current iteration (used to truncate the tokens array)
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int result_len;
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double sum_logprobs_all; // the sum of the log probabilities of the tokens

whisper.h

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@@ -346,7 +346,7 @@ extern "C" {
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void * user_data);
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// Parameters for the whisper_full() function
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// If you chnage the order or add new parameters, make sure to update the default values in whisper.cpp:
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// If you change the order or add new parameters, make sure to update the default values in whisper.cpp:
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// whisper_full_default_params()
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struct whisper_full_params {
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enum whisper_sampling_strategy strategy;

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