Instructions to use Rajaram1996/Hubert_emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rajaram1996/Hubert_emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Rajaram1996/Hubert_emotion")# Load model directly from transformers import AutoProcessor, HubertForSpeechClassification processor = AutoProcessor.from_pretrained("Rajaram1996/Hubert_emotion") model = HubertForSpeechClassification.from_pretrained("Rajaram1996/Hubert_emotion") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "facebook/hubert-base-ls960", | |
| "activation_dropout": 0.1, | |
| "apply_spec_augment": true, | |
| "architectures": [ | |
| "HubertForSpeechClassification" | |
| ], | |
| "attention_dropout": 0.1, | |
| "bos_token_id": 1, | |
| "classifier_proj_size": 256, | |
| "conv_bias": false, | |
| "conv_dim": [ | |
| 512, | |
| 512, | |
| 512, | |
| 512, | |
| 512, | |
| 512, | |
| 512 | |
| ], | |
| "conv_kernel": [ | |
| 10, | |
| 3, | |
| 3, | |
| 3, | |
| 3, | |
| 2, | |
| 2 | |
| ], | |
| "conv_stride": [ | |
| 5, | |
| 2, | |
| 2, | |
| 2, | |
| 2, | |
| 2, | |
| 2 | |
| ], | |
| "ctc_loss_reduction": "sum", | |
| "ctc_zero_infinity": false, | |
| "do_stable_layer_norm": false, | |
| "eos_token_id": 2, | |
| "feat_extract_activation": "gelu", | |
| "feat_extract_dropout": 0.0, | |
| "feat_extract_norm": "group", | |
| "feat_proj_dropout": 0.1, | |
| "final_dropout": 0.1, | |
| "finetuning_task": "wav2vec2_clf", | |
| "gradient_checkpointing": false, | |
| "hidden_act": "gelu", | |
| "hidden_dropout": 0.1, | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "female_angry", | |
| "1": "female_disgust", | |
| "2": "female_fear", | |
| "3": "female_happy", | |
| "4": "female_neutral", | |
| "5": "female_sad", | |
| "6": "female_surprise", | |
| "7": "male_angry", | |
| "8": "male_disgust", | |
| "9": "male_fear", | |
| "10": "male_happy", | |
| "11": "male_neutral", | |
| "12": "male_sad", | |
| "13": "male_surprise" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "female_angry": 0, | |
| "female_disgust": 1, | |
| "female_fear": 2, | |
| "female_happy": 3, | |
| "female_neutral": 4, | |
| "female_sad": 5, | |
| "female_surprise": 6, | |
| "male_angry": 7, | |
| "male_disgust": 8, | |
| "male_fear": 9, | |
| "male_happy": 10, | |
| "male_neutral": 11, | |
| "male_sad": 12, | |
| "male_surprise": 13 | |
| }, | |
| "layer_norm_eps": 1e-05, | |
| "layerdrop": 0.1, | |
| "mask_feature_length": 10, | |
| "mask_feature_prob": 0.0, | |
| "mask_time_length": 10, | |
| "mask_time_prob": 0.05, | |
| "model_type": "hubert", | |
| "num_attention_heads": 12, | |
| "num_conv_pos_embedding_groups": 16, | |
| "num_conv_pos_embeddings": 128, | |
| "num_feat_extract_layers": 7, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 0, | |
| "pooling_mode": "mean", | |
| "problem_type": "single_label_classification", | |
| "tokenizer_class": "Wav2Vec2CTCTokenizer", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.12.0.dev0", | |
| "use_weighted_layer_sum": false, | |
| "vocab_size": 32 | |
| } | |