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{ |
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"models": { |
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"whisper": [ |
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// Configuration for the built-in models. You can remove any of these |
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// if you don't want to use the default models. |
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{ |
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"name": "tiny", |
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"url": "tiny" |
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}, |
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{ |
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"name": "base", |
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"url": "base" |
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}, |
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{ |
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"name": "small", |
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"url": "small" |
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}, |
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{ |
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"name": "medium", |
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"url": "medium" |
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}, |
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{ |
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"name": "large", |
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"url": "large" |
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}, |
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{ |
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"name": "large-v1", |
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"url": "large-v1" |
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}, |
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{ |
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"name": "large-v2", |
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"url": "large-v2" |
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}, |
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{ |
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"name": "large-v3", |
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"url": "large-v3" |
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} |
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// Uncomment to add custom Japanese models |
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//{ |
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// "name": "whisper-large-v2-mix-jp", |
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// "url": "vumichien/whisper-large-v2-mix-jp", |
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// // The type of the model. Can be "huggingface" or "whisper" - "whisper" is the default. |
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// // HuggingFace models are loaded using the HuggingFace transformers library and then converted to Whisper models. |
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// "type": "huggingface", |
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//}, |
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//{ |
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// "name": "local-model", |
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// "url": "path/to/local/model", |
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//}, |
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//{ |
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// "name": "remote-model", |
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// "url": "https://example.com/path/to/model", |
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//} |
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], |
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"m2m100": [ |
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{ |
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"name": "m2m100_1.2B-ct2fast/michaelfeil", |
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"url": "michaelfeil/ct2fast-m2m100_1.2B", |
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"type": "huggingface", |
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"tokenizer_url": "facebook/m2m100_1.2B" |
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}, |
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{ |
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"name": "m2m100_418M-ct2fast/michaelfeil", |
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"url": "michaelfeil/ct2fast-m2m100_418M", |
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"type": "huggingface", |
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"tokenizer_url": "facebook/m2m100_418M" |
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}, |
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//{ |
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// "name": "m2m100-12B-ct2fast/michaelfeil", |
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// "url": "michaelfeil/ct2fast-m2m100-12B-last-ckpt", |
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// "type": "huggingface", |
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// "tokenizer_url": "facebook/m2m100-12B-last-ckpt" |
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//}, |
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{ |
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"name": "m2m100_1.2B/facebook", |
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"url": "facebook/m2m100_1.2B", |
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"type": "huggingface" |
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}, |
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{ |
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"name": "m2m100_418M/facebook", |
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"url": "facebook/m2m100_418M", |
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"type": "huggingface" |
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} |
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], |
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"nllb": [ |
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{ |
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"name": "nllb-200-distilled-1.3B-ct2fast:int8_float16/michaelfeil", |
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"url": "michaelfeil/ct2fast-nllb-200-distilled-1.3B", |
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"type": "huggingface", |
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"tokenizer_url": "facebook/nllb-200-distilled-1.3B" |
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}, |
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{ |
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"name": "nllb-200-3.3B-ct2fast:int8_float16/michaelfeil", |
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"url": "michaelfeil/ct2fast-nllb-200-3.3B", |
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"type": "huggingface", |
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"tokenizer_url": "facebook/nllb-200-3.3B" |
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}, |
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{ |
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"name": "nllb-200-1.3B-ct2:float16/JustFrederik", |
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"url": "JustFrederik/nllb-200-1.3B-ct2-float16", |
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"type": "huggingface", |
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"tokenizer_url": "facebook/nllb-200-1.3B" |
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}, |
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{ |
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"name": "nllb-200-distilled-1.3B-ct2:float16/JustFrederik", |
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"url": "JustFrederik/nllb-200-distilled-1.3B-ct2-float16", |
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"type": "huggingface", |
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"tokenizer_url": "facebook/nllb-200-distilled-1.3B" |
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}, |
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{ |
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"name": "nllb-200-1.3B-ct2:int8/JustFrederik", |
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"url": "JustFrederik/nllb-200-1.3B-ct2-int8", |
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"type": "huggingface", |
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"tokenizer_url": "facebook/nllb-200-1.3B" |
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}, |
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{ |
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"name": "nllb-200-distilled-1.3B-ct2:int8/JustFrederik", |
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"url": "JustFrederik/nllb-200-distilled-1.3B-ct2-int8", |
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"type": "huggingface", |
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"tokenizer_url": "facebook/nllb-200-distilled-1.3B" |
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}, |
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{ |
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"name": "nllb-200-distilled-600M/facebook", |
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"url": "facebook/nllb-200-distilled-600M", |
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"type": "huggingface" |
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}, |
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{ |
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"name": "nllb-200-distilled-600M-ct2/JustFrederik", |
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"url": "JustFrederik/nllb-200-distilled-600M-ct2", |
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"type": "huggingface", |
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"tokenizer_url": "facebook/nllb-200-distilled-600M" |
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}, |
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{ |
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"name": "nllb-200-distilled-600M-ct2:float16/JustFrederik", |
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"url": "JustFrederik/nllb-200-distilled-600M-ct2-float16", |
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"type": "huggingface", |
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"tokenizer_url": "facebook/nllb-200-distilled-600M" |
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}, |
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{ |
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"name": "nllb-200-distilled-600M-ct2:int8/JustFrederik", |
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"url": "JustFrederik/nllb-200-distilled-600M-ct2-int8", |
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"type": "huggingface", |
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"tokenizer_url": "facebook/nllb-200-distilled-600M" |
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} |
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// Uncomment to add official Facebook 1.3B and 3.3B model |
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// The official Facebook 1.3B and 3.3B model files are too large, |
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// and to avoid occupying too much disk space on Hugging Face's free spaces, |
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// these models are not included in the config. |
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//{ |
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// "name": "nllb-200-distilled-1.3B/facebook", |
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// "url": "facebook/nllb-200-distilled-1.3B", |
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// "type": "huggingface" |
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//}, |
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//{ |
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// "name": "nllb-200-1.3B/facebook", |
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// "url": "facebook/nllb-200-1.3B", |
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// "type": "huggingface" |
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//}, |
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//{ |
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// "name": "nllb-200-3.3B/facebook", |
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// "url": "facebook/nllb-200-3.3B", |
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// "type": "huggingface" |
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//}, |
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//{ |
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// "name": "nllb-200-distilled-1.3B-ct2/JustFrederik", |
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// "url": "JustFrederik/nllb-200-distilled-1.3B-ct2", |
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// "type": "huggingface", |
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// "tokenizer_url": "facebook/nllb-200-distilled-1.3B" |
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//}, |
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//{ |
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// "name": "nllb-200-1.3B-ct2/JustFrederik", |
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// "url": "JustFrederik/nllb-200-1.3B-ct2", |
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// "type": "huggingface", |
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// "tokenizer_url": "facebook/nllb-200-1.3B" |
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//}, |
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//{ |
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// "name": "nllb-200-3.3B-ct2:float16/JustFrederik", |
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// "url": "JustFrederik/nllb-200-3.3B-ct2-float16", |
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// "type": "huggingface", |
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// "tokenizer_url": "facebook/nllb-200-3.3B" |
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//}, |
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], |
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"mt5": [ |
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{ |
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"name": "mt5-zh-ja-en-trimmed/K024", |
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"url": "K024/mt5-zh-ja-en-trimmed", |
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"type": "huggingface" |
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}, |
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{ |
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"name": "mt5-zh-ja-en-trimmed-fine-tuned-v1/engmatic-earth", |
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"url": "engmatic-earth/mt5-zh-ja-en-trimmed-fine-tuned-v1", |
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"type": "huggingface" |
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} |
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], |
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"ALMA": [ |
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{ |
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"name": "ALMA-7B-GPTQ/TheBloke", |
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"url": "TheBloke/ALMA-7B-GPTQ", |
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"type": "huggingface" |
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}, |
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{ |
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"name": "ALMA-13B-GPTQ/TheBloke", |
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"url": "TheBloke/ALMA-13B-GPTQ", |
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"type": "huggingface" |
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}, |
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{ |
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"name": "ALMA-7B-GGUF-Q4_K_M/TheBloke", |
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"url": "TheBloke/ALMA-7B-GGUF", |
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"type": "huggingface", |
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"model_file": "alma-7b.Q4_K_M.gguf", |
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"tokenizer_url": "haoranxu/ALMA-7B" |
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}, |
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{ |
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"name": "ALMA-13B-GGUF-Q4_K_M/TheBloke", |
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"url": "TheBloke/ALMA-13B-GGUF", |
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"type": "huggingface", |
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"model_file": "alma-13b.Q4_K_M.gguf", |
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"tokenizer_url": "haoranxu/ALMA-13B" |
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}, |
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{ |
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"name": "ALMA-7B-ct2:int8_float16/avan", |
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"url": "avans06/ALMA-7B-ct2-int8_float16", |
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"type": "huggingface", |
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"tokenizer_url": "haoranxu/ALMA-7B" |
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}, |
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{ |
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"name": "ALMA-13B-ct2:int8_float16/avan", |
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"url": "avans06/ALMA-13B-ct2-int8_float16", |
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"type": "huggingface", |
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"tokenizer_url": "haoranxu/ALMA-13B" |
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}, |
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] |
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}, |
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// Configuration options that will be used if they are not specified in the command line arguments. |
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|
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// * WEBUI options * |
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|
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// Maximum audio file length in seconds, or -1 for no limit. Ignored by CLI. |
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"input_audio_max_duration": 1800, |
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// True to share the app on HuggingFace. |
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"share": false, |
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// The host or IP to bind to. If None, bind to localhost. |
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"server_name": null, |
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// The port to bind to. |
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"server_port": 7860, |
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// The number of workers to use for the web server. Use -1 to disable queueing. |
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"queue_concurrency_count": 1, |
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// Whether or not to automatically delete all uploaded files, to save disk space |
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"delete_uploaded_files": true, |
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|
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// * General options * |
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|
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// The default implementation to use for Whisper. Can be "whisper" or "faster-whisper". |
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// Note that you must either install the requirements for faster-whisper (requirements-fasterWhisper.txt) |
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// or whisper (requirements.txt) |
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"whisper_implementation": "faster-whisper", |
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|
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// The default model name. |
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"default_model_name": "large-v2", |
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// The default VAD. |
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"default_vad": "silero-vad", |
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// A commma delimited list of CUDA devices to use for parallel processing. If None, disable parallel processing. |
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"vad_parallel_devices": "", |
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// The number of CPU cores to use for VAD pre-processing. |
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"vad_cpu_cores": 1, |
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// The number of seconds before inactivate processes are terminated. Use 0 to close processes immediately, or None for no timeout. |
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"vad_process_timeout": 1800, |
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// True to use all available GPUs and CPU cores for processing. Use vad_cpu_cores/vad_parallel_devices to specify the number of CPU cores/GPUs to use. |
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"auto_parallel": false, |
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// Directory to save the outputs (CLI will use the current directory if not specified) |
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"output_dir": null, |
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// The path to save model files; uses ~/.cache/whisper by default |
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"model_dir": null, |
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// Device to use for PyTorch inference, or Null to use the default device |
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"device": null, |
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// Whether to print out the progress and debug messages |
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"verbose": true, |
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// Whether to perform X->X speech recognition ('transcribe') or X->English translation ('translate') |
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"task": "transcribe", |
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// Language spoken in the audio, specify None to perform language detection |
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"language": null, |
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// The window size (in seconds) to merge voice segments |
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"vad_merge_window": 5, |
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// The maximum size (in seconds) of a voice segment |
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"vad_max_merge_size": 90, |
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// The padding (in seconds) to add to each voice segment |
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"vad_padding": 1, |
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// Whether or not to prepend the initial prompt to each VAD segment (prepend_all_segments), or just the first segment (prepend_first_segment) |
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"vad_initial_prompt_mode": "prepend_first_segment", |
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// The window size of the prompt to pass to Whisper |
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"vad_prompt_window": 3, |
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// Temperature to use for sampling |
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"temperature": 0, |
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// Number of candidates when sampling with non-zero temperature |
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"best_of": 5, |
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// Number of beams in beam search, only applicable when temperature is zero |
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"beam_size": 5, |
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// Optional patience value to use in beam decoding, as in https://arxiv.org/abs/2204.05424, the default (1.0) is equivalent to conventional beam search |
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"patience": 1, |
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// Optional token length penalty coefficient (alpha) as in https://arxiv.org/abs/1609.08144, uses simple length normalization by default |
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"length_penalty": null, |
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// Comma-separated list of token ids to suppress during sampling; '-1' will suppress most special characters except common punctuations |
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"suppress_tokens": "-1", |
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// Optional text to provide as a prompt for the first window |
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"initial_prompt": null, |
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// If True, provide the previous output of the model as a prompt for the next window; disabling may make the text inconsistent across windows, but the model becomes less prone to getting stuck in a failure loop |
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"condition_on_previous_text": true, |
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// Whether to perform inference in fp16; True by default |
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"fp16": true, |
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// The compute type used by faster-whisper. Can be "int8". "int16" or "float16". |
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"compute_type": "auto", |
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// Temperature to increase when falling back when the decoding fails to meet either of the thresholds below |
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"temperature_increment_on_fallback": 0.2, |
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// If the gzip compression ratio is higher than this value, treat the decoding as failed |
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"compression_ratio_threshold": 2.4, |
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// If the average log probability is lower than this value, treat the decoding as failed |
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"logprob_threshold": -1.0, |
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// If the probability of the <no-speech> token is higher than this value AND the decoding has failed due to `logprob_threshold`, consider the segment as silence |
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"no_speech_threshold": 0.6, |
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// [faster-whisper] The parameter for repetition penalty. Between 1.0 and infinity. 1.0 means no penalty. Default to 1.0. |
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"repetition_penalty": 1.0, |
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// [faster-whisper] The model ensures that a sequence of words of no_repeat_ngram_size isn’t repeated in the output sequence. If specified, it must be a positive integer greater than 1. |
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"no_repeat_ngram_size": 0, |
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|
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// (experimental) extract word-level timestamps and refine the results based on them |
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"word_timestamps": true, |
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// if word_timestamps is True, merge these punctuation symbols with the next word |
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"prepend_punctuations": "\"\'“¿([{-", |
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// if word_timestamps is True, merge these punctuation symbols with the previous word |
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"append_punctuations": "\"\'.。,,!!??::”)]}、", |
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// (requires --word_timestamps True) underline each word as it is spoken in srt and vtt |
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"highlight_words": false, |
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|
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// Diarization settings |
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"auth_token": null, |
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// Whether to perform speaker diarization |
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"diarization": false, |
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// The number of speakers to detect |
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"diarization_speakers": 2, |
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// The minimum number of speakers to detect |
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"diarization_min_speakers": 1, |
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// The maximum number of speakers to detect |
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"diarization_max_speakers": 8, |
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// The number of seconds before inactivate processes are terminated. Use 0 to close processes immediately, or None for no timeout. |
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"diarization_process_timeout": 60, |
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|
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// Whisper Segments Filter |
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"whisper_segments_filter": false, |
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"whisper_segments_filters": [ |
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"avg_logprob < -0.9", |
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"(durationLen < 1.5 || segment_last), textLen > 5, avg_logprob < -0.4, no_speech_prob > 0.5", |
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"(durationLen < 1.5 || segment_last), textLen > 5, avg_logprob < -0.4, no_speech_prob > 0.07, compression_ratio < 0.9", |
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"(durationLen < 1.5 || segment_last), compression_ratio < 0.9, no_speech_prob > 0.1" |
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], |
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|
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// Translation - The maximum batch size. |
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"translation_batch_size": 2, |
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// Translation - Prevent repetitions of ngrams with this size (set 0 to disable). |
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"translation_no_repeat_ngram_size": 3, |
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// Translation - Beam size (1 for greedy search). |
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"translation_num_beams": 2, |
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} |