Instructions to use 1Developer/cali-ast-wakeword with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 1Developer/cali-ast-wakeword with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="1Developer/cali-ast-wakeword")# pip install -U transformers accelerate # Load model directly from transformers import AutoFeatureExtractor, AutoModelForAudioClassification extractor = AutoFeatureExtractor.from_pretrained("1Developer/cali-ast-wakeword") model = AutoModelForAudioClassification.from_pretrained("1Developer/cali-ast-wakeword", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from 1Developer/cali-ast-wakeword: direct link, hf CLI and curl.
- Browser
- Download file 809 Bytes
-
https://huggingface.co/1Developer/cali-ast-wakeword/resolve/main/config.json
- Command line
-
hf download hf://1Developer/cali-ast-wakeword/config.json
-
curl -L -o config.json https://huggingface.co/1Developer/cali-ast-wakeword/resolve/main/config.json
809 Bytes
| { | |
| "architectures": [ | |
| "ASTForAudioClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.0, | |
| "dtype": "float32", | |
| "frequency_stride": 10, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.0, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "cali", | |
| "1": "calista", | |
| "2": "unknown" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "cali": 0, | |
| "calista": 1, | |
| "unknown": 2 | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "max_length": 128, | |
| "model_type": "audio-spectrogram-transformer", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "num_mel_bins": 128, | |
| "patch_size": 16, | |
| "problem_type": "single_label_classification", | |
| "qkv_bias": true, | |
| "time_stride": 10, | |
| "transformers_version": "5.14.1", | |
| "use_cache": false | |
| } | |