Bofenghuang
Rank:Average Model Cost: $0.0000
Number of Runs: 4,122
Models by this creator
whisper-small-cv11-german
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1.2K
Huggingface
whisper-large-v2-cv11-german
whisper-large-v2-cv11-german
Platform did not provide a description for this model.
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769
Huggingface
whisper-medium-cv11-german
whisper-medium-cv11-german
Platform did not provide a description for this model.
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761
Huggingface
asr-wav2vec2-ctc-french
asr-wav2vec2-ctc-french
Fine-tuned wav2vec2-FR-7K-large model for ASR in French This model is a fine-tuned version of LeBenchmark/wav2vec2-FR-7K-large, trained on a composite dataset comprising of over 2200 hours of French speech audio, using the train and validation splits of Common Voice 11.0, Multilingual LibriSpeech, Voxpopuli, Multilingual TEDx, MediaSpeech, and African Accented French. When using the model make sure that your speech input is also sampled at 16Khz. Usage To use on a local audio file with the language model To use on a local audio file without the language model Evaluation To evaluate on mozilla-foundation/common_voice_11_0 To evaluate on speech-recognition-community-v2/dev_data
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383
Huggingface
whisper-large-v2-cv11-french
whisper-large-v2-cv11-french
Fine-tuned whisper-large-v2 model for ASR in French This model is a fine-tuned version of openai/whisper-large-v2, trained on the mozilla-foundation/common_voice_11_0 fr dataset. When using the model make sure that your speech input is also sampled at 16Khz. This model also predicts casing and punctuation. Performance Below are the WERs of the pre-trained models on the Common Voice 9.0, Multilingual LibriSpeech, Voxpopuli and Fleurs. These results are reported in the original paper. Below are the WERs of the fine-tuned models on the Common Voice 11.0, Multilingual LibriSpeech, Voxpopuli, and Fleurs. Note that these evaluation datasets have been filtered and preprocessed to only contain French alphabet characters and are removed of punctuation outside of apostrophe. The results in the table are reported as WER (greedy search) / WER (beam search with beam width 5). Usage Inference with 🤗 Pipeline Inference with 🤗 low-level APIs
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261
Huggingface
whisper-large-v2-french
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225
Huggingface
whisper-medium-french
whisper-medium-french
Fine-tuned whisper-medium model for ASR in French This model is a fine-tuned version of openai/whisper-medium, trained on a composite dataset comprising of over 2200 hours of French speech audio, using the train and the validation splits of Common Voice 11.0, Multilingual LibriSpeech, Voxpopuli, Fleurs, Multilingual TEDx, MediaSpeech, and African Accented French. When using the model make sure that your speech input is sampled at 16Khz. This model doesn't predict casing or punctuation. Performance Below are the WERs of the pre-trained models on the Common Voice 9.0, Multilingual LibriSpeech, Voxpopuli and Fleurs. These results are reported in the original paper. Below are the WERs of the fine-tuned models on the Common Voice 11.0, Multilingual LibriSpeech, Voxpopuli, and Fleurs. Note that these evaluation datasets have been filtered and preprocessed to only contain French alphabet characters and are removed of punctuation outside of apostrophe. The results in the table are reported as WER (greedy search) / WER (beam search with beam width 5). Usage Inference with 🤗 Pipeline Inference with 🤗 low-level APIs
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189
Huggingface
vigogne-falcon-7b-chat
vigogne-falcon-7b-chat
Vigogne-Falcon-7B-Chat: A French Chat Falcon Model Vigogne-Falcon-7B-Chat is a Falcon-7B model fine-tuned to conduct multi-turn dialogues in French between human user and AI assistant. For more information, please visit the Github repo: https://github.com/bofenghuang/vigogne Changelog All versions are available in branches. V1.0: Initial release. V2.0: Expanded training dataset to 419k for better performance. Usage Limitations Vigogne is still under development, and there are many limitations that have to be addressed. Please note that it is possible that the model generates harmful or biased content, incorrect information or generally unhelpful answers.
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146
Huggingface
flan-t5-large-french-dialogue-summarization
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83
Huggingface
whisper-medium-cv11-french
whisper-medium-cv11-french
Fine-tuned whisper-medium model for ASR in French This model is a fine-tuned version of openai/whisper-medium, trained on the mozilla-foundation/common_voice_11_0 fr dataset. When using the model make sure that your speech input is also sampled at 16Khz. This model also predicts casing and punctuation. Performance Below are the WERs of the pre-trained models on the Common Voice 9.0, Multilingual LibriSpeech, Voxpopuli and Fleurs. These results are reported in the original paper. Below are the WERs of the fine-tuned models on the Common Voice 11.0, Multilingual LibriSpeech, Voxpopuli, and Fleurs. Note that these evaluation datasets have been filtered and preprocessed to only contain French alphabet characters and are removed of punctuation outside of apostrophe. The results in the table are reported as WER (greedy search) / WER (beam search with beam width 5). Usage Inference with 🤗 Pipeline Inference with 🤗 low-level APIs
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70
Huggingface