Instructions to use VasilisAsim/data2vec-finetuned-IEMOCAP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VasilisAsim/data2vec-finetuned-IEMOCAP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="VasilisAsim/data2vec-finetuned-IEMOCAP")# Load model directly from transformers import AutoTokenizer, AutoModelForAudioClassification tokenizer = AutoTokenizer.from_pretrained("VasilisAsim/data2vec-finetuned-IEMOCAP") model = AutoModelForAudioClassification.from_pretrained("VasilisAsim/data2vec-finetuned-IEMOCAP", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "activation_dropout": 0.1, | |
| "adapter_kernel_size": 3, | |
| "adapter_stride": 2, | |
| "add_adapter": false, | |
| "architectures": [ | |
| "Data2VecAudioForSequenceClassification" | |
| ], | |
| "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_pos_kernel_size": 19, | |
| "conv_stride": [ | |
| 5, | |
| 2, | |
| 2, | |
| 2, | |
| 2, | |
| 2, | |
| 2 | |
| ], | |
| "ctc_loss_reduction": "sum", | |
| "ctc_zero_infinity": false, | |
| "dtype": "float32", | |
| "eos_token_id": 2, | |
| "feat_extract_activation": "gelu", | |
| "feat_proj_dropout": 0.0, | |
| "final_dropout": 0.1, | |
| "hidden_act": "gelu", | |
| "hidden_dropout": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "ang", | |
| "1": "dis", | |
| "2": "exc", | |
| "3": "fea", | |
| "4": "fru", | |
| "5": "hap", | |
| "6": "neu", | |
| "7": "oth", | |
| "8": "sad", | |
| "9": "sur" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "ang": 0, | |
| "dis": 1, | |
| "exc": 2, | |
| "fea": 3, | |
| "fru": 4, | |
| "hap": 5, | |
| "neu": 6, | |
| "oth": 7, | |
| "sad": 8, | |
| "sur": 9 | |
| }, | |
| "layer_norm_eps": 1e-05, | |
| "layerdrop": 0.1, | |
| "mask_feature_length": 10, | |
| "mask_feature_min_masks": 0, | |
| "mask_feature_prob": 0.0, | |
| "mask_time_length": 10, | |
| "mask_time_min_masks": 2, | |
| "mask_time_prob": 0.05, | |
| "model_type": "data2vec-audio", | |
| "num_adapter_layers": 3, | |
| "num_attention_heads": 12, | |
| "num_conv_pos_embedding_groups": 16, | |
| "num_conv_pos_embeddings": 5, | |
| "num_feat_extract_layers": 7, | |
| "num_hidden_layers": 12, | |
| "output_hidden_size": 768, | |
| "pad_token_id": 0, | |
| "tdnn_dilation": [ | |
| 1, | |
| 2, | |
| 3, | |
| 1, | |
| 1 | |
| ], | |
| "tdnn_dim": [ | |
| 512, | |
| 512, | |
| 512, | |
| 512, | |
| 1500 | |
| ], | |
| "tdnn_kernel": [ | |
| 5, | |
| 3, | |
| 3, | |
| 1, | |
| 1 | |
| ], | |
| "transformers_version": "5.12.0", | |
| "use_cache": false, | |
| "use_weighted_layer_sum": false, | |
| "vocab_size": 32, | |
| "xvector_output_dim": 512 | |
| } | |