Instructions to use hsali/wav2vec2_e_emo__d100 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hsali/wav2vec2_e_emo__d100 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, Wav2Vec2ForSpeechClassification processor = AutoProcessor.from_pretrained("hsali/wav2vec2_e_emo__d100") model = Wav2Vec2ForSpeechClassification.from_pretrained("hsali/wav2vec2_e_emo__d100", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from hsali/wav2vec2_e_emo__d100: direct link, hf CLI and curl.
- Browser
- Download file 618 Bytes
-
https://huggingface.co/hsali/wav2vec2_e_emo__d100/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://hsali/wav2vec2_e_emo__d100/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/hsali/wav2vec2_e_emo__d100/resolve/main/tokenizer_config.json
618 Bytes
| { | |
| "bos_token": "<s>", | |
| "do_lower_case": false, | |
| "do_normalize": true, | |
| "eos_token": "</s>", | |
| "model_max_length": 9223372036854775807, | |
| "name_or_path": "facebook/wav2vec2-base-960h", | |
| "pad_token": "<pad>", | |
| "processor_class": "Wav2Vec2Processor", | |
| "replace_word_delimiter_char": " ", | |
| "return_attention_mask": false, | |
| "special_tokens_map_file": "C:\\Users\\hafiz/.cache\\huggingface\\hub\\models--facebook--wav2vec2-base-960h\\snapshots\\22aad52d435eb6dbaf354bdad9b0da84ce7d6156\\special_tokens_map.json", | |
| "tokenizer_class": "Wav2Vec2CTCTokenizer", | |
| "unk_token": "<unk>", | |
| "word_delimiter_token": "|" | |
| } | |