mistral-pl-owca
JonaszPotoniec基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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探索 AI 模型 84999
wav2vec2-large-xlsr-53-arabic
jonatasgrosmanFine-tuned facebook/wav2vec2-large-xlsr-53 on Arabic using the train and validation splits of Common Voice 6.1 and Arabic Speech Corpus. When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned thanks to the GPU credits generously given by the OVHcloud :) The script used for training can be found here: https://github.com/jonatasgrosman/wav2vec2-sprint
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查看详情 ↗wav2vec2-large-xlsr-53-chinese-zh-cn
jonatasgrosmanFine-tuned facebook/wav2vec2-large-xlsr-53 on Chinese using the train and validation splits of Common Voice 6.1, CSS10 and ST-CMDS. When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned thanks to the GPU credits generously given by the OVHcloud :) The script used for training can be found here: https://github.com/jonatasgrosman/wav2vec2-sprint
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查看详情 ↗wav2vec2-large-xlsr-53-dutch
jonatasgrosmanFine-tuned facebook/wav2vec2-large-xlsr-53 on Dutch using the train and validation splits of Common Voice 6.1 and CSS10. When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned thanks to the GPU credits generously given by the OVHcloud :) The script used for training can be found here: https://github.com/jonatasgrosman/wav2vec2-sprint
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查看详情 ↗wav2vec2-large-xlsr-53-english
jonatasgrosmanFine-tuned facebook/wav2vec2-large-xlsr-53 on English using the train and validation splits of Common Voice 6.1. When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned thanks to the GPU credits generously given by the OVHcloud :) The script used for training can be found here: https://github.com/jonatasgrosman/wav2vec2-sprint
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查看详情 ↗wav2vec2-large-xlsr-53-finnish
jonatasgrosmanFine-tuned facebook/wav2vec2-large-xlsr-53 on Finnish using the train and validation splits of Common Voice 6.1 and CSS10. When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned thanks to the GPU credits generously given by the OVHcloud :) The script used for training can be found here: https://github.com/jonatasgrosman/wav2vec2-sprint
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查看详情 ↗wav2vec2-large-xlsr-53-french
jonatasgrosmanFine-tuned facebook/wav2vec2-large-xlsr-53 on French using the train and validation splits of Common Voice 6.1. When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned thanks to the GPU credits generously given by the OVHcloud :) The script used for training can be found here: https://github.com/jonatasgrosman/wav2vec2-sprint
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查看详情 ↗wav2vec2-large-xlsr-53-german
jonatasgrosmanFine-tuned facebook/wav2vec2-large-xlsr-53 on German using the train and validation splits of Common Voice 6.1. When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned thanks to the GPU credits generously given by the OVHcloud :) The script used for training can be found here: https://github.com/jonatasgrosman/wav2vec2-sprint
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查看详情 ↗wav2vec2-large-xlsr-53-greek
jonatasgrosmanFine-tuned facebook/wav2vec2-large-xlsr-53 on Greek using the train and validation splits of Common Voice 6.1 and CSS10. When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned thanks to the GPU credits generously given by the OVHcloud :) The script used for training can be found here: https://github.com/jonatasgrosman/wav2vec2-sprint
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查看详情 ↗wav2vec2-large-xlsr-53-hungarian
jonatasgrosmanFine-tuned facebook/wav2vec2-large-xlsr-53 on Hungarian using the train and validation splits of Common Voice 6.1 and CSS10. When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned thanks to the GPU credits generously given by the OVHcloud :) The script used for training can be found here: https://github.com/jonatasgrosman/wav2vec2-sprint
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查看详情 ↗wav2vec2-large-xlsr-53-italian
jonatasgrosmanFine-tuned facebook/wav2vec2-large-xlsr-53 on Italian using the train and validation splits of Common Voice 6.1. When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned thanks to the GPU credits generously given by the OVHcloud :) The script used for training can be found here: https://github.com/jonatasgrosman/wav2vec2-sprint
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查看详情 ↗wav2vec2-large-xlsr-53-japanese
jonatasgrosman使用 Common Voice 6.1、CSS10 和 JSUT 的训练集与验证集，在日语上对 facebook/wav2vec2-large-xlsr-53 进行了微调。使用该模型时，请确保您的语音输入采样率为 16kHz。下表报告了该模型的词错误率（WER）和字符错误率（CER）。我还于 2021-05-10 对其他模型运行了上述评估脚本。请注意，下表显示的结果可能与先前报告的不同，这可能是由于所用其他评估脚本存在某些特定差异所致。
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查看详情 ↗wav2vec2-large-xlsr-53-persian
jonatasgrosmanFine-tuned facebook/wav2vec2-large-xlsr-53 on Persian using the train and validation splits of Common Voice 6.1. When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned thanks to the GPU credits generously given by the OVHcloud :) The script used for training can be found here: https://github.com/jonatasgrosman/wav2vec2-sprint
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查看详情 ↗wav2vec2-large-xlsr-53-polish
jonatasgrosmanFine-tuned facebook/wav2vec2-large-xlsr-53 on Polish using the train and validation splits of Common Voice 6.1. When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned thanks to the GPU credits generously given by the OVHcloud :) The script used for training can be found here: https://github.com/jonatasgrosman/wav2vec2-sprint
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查看详情 ↗wav2vec2-large-xlsr-53-portuguese
jonatasgrosman使用 Common Voice 6.1 的训练集和验证集，在葡萄牙语上对 facebook/wav2vec2-large-xlsr-53 进行了微调。使用该模型时，请确保您的语音输入采样率为 16kHz。
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查看详情 ↗wav2vec2-large-xlsr-53-russian
jonatasgrosman使用 Common Voice 6.1 和 CSS10 的训练集与验证集，在俄语上对 facebook/wav2vec2-large-xlsr-53 进行了微调。使用该模型时，请确保您的语音输入采样率为 16kHz。
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价格待核验多模态与渠道费用须分别核对
查看详情 ↗wav2vec2-large-xlsr-53-spanish
jonatasgrosmanFine-tuned facebook/wav2vec2-large-xlsr-53 on Spanish using the train and validation splits of Common Voice 6.1. When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned thanks to the GPU credits generously given by the OVHcloud :) The script used for training can be found here: https://github.com/jonatasgrosman/wav2vec2-sprint
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查看详情 ↗wav2vec2-xls-r-1b-english
jonatasgrosman基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
基础资料已收录 · 缺失资料后续补充
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查看详情 ↗wav2vec2-xls-r-1b-french
jonatasgrosman基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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查看详情 ↗wav2vec2-xls-r-1b-german
jonatasgrosman基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
基础资料已收录 · 缺失资料后续补充
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查看详情 ↗wav2vec2-xls-r-1b-portuguese
jonatasgrosmanFine-tuned facebook/wav2vec2-xls-r-1b on Portuguese using the train and validation splits of Common Voice 8.0, CORAA, Multilingual TEDx, and Multilingual LibriSpeech. When using this model, make sure that your speech input is sampled at 16kHz. This model has been fine-tuned by the HuggingSound tool, and thanks to the GPU credits generously given by the OVHcloud :) Using the HuggingSound library:
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查看详情 ↗wav2vec2-xls-r-1b-russian
jonatasgrosman基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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价格待核验多模态与渠道费用须分别核对
查看详情 ↗wav2vec2-xls-r-1b-spanish
jonatasgrosman基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
基础资料已收录 · 缺失资料后续补充
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查看详情 ↗swift15-gsq-rco-iq3s-mtp
jonathan-golden基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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输入 待核验→ 输出 待核验
价格待核验多模态与渠道费用须分别核对
查看详情 ↗暂未找到匹配模型
可以调整厂商、分类或输入输出条件；新模型正持续收录。
COST EXPLORER
好模型，也要算好成本。
调整月度 Token 用量，直观比较不同模型的预估 API 开支。
1 M = 100 万 Token · 美元计价
仅比较同一渠道的基础文本 Token 报价
仅比较同一渠道的基础文本 Token 报价
使用已采集且单位可比的 USD / 百万 Token 渠道报价。报价为采集时快照；不计缓存优惠、阶梯价、推理额外输出与税费，请以来源的当前报价为准。
MODEL HANDBOOK
读懂模型，再做选择
API 价格应该怎么比较？+
先区分输入、输出和缓存价格，再使用同一任务和用量估算总费用。图像、音频和视频可能按张、时长或分辨率计费，不能直接与 Token 单价比较。
开放权重，就代表可以免费商用吗？+
不一定。必须逐一核对具体模型版本的许可证、商用限制及使用政策。自己部署还需要考虑显存、推理资源和运维费用。
排行榜第一，就是最适合我的模型吗？+
榜单取决于测试任务、版本与评测方法。建议用实际业务样本比较准确性、时延、稳定性和成本，再选择模型。