Audio Classification
Transformers
Safetensors
PyTorch
ONNX
English
wav2vec2
audio
keyword-spotting
kws
sagemaker
streaming-inference
realtime
Instructions to use Amirhossein75/Keyword-Spotting with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Amirhossein75/Keyword-Spotting with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Amirhossein75/Keyword-Spotting")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Amirhossein75/Keyword-Spotting") model = AutoModelForAudioClassification.from_pretrained("Amirhossein75/Keyword-Spotting", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download vocab.json from Amirhossein75/Keyword-Spotting: direct link, hf CLI and curl.
- Browser
- Download file 291 Bytes
-
https://huggingface.co/Amirhossein75/Keyword-Spotting/resolve/main/vocab.json
- Command line
-
hf download hf://Amirhossein75/Keyword-Spotting/vocab.json
-
curl -L -o vocab.json https://huggingface.co/Amirhossein75/Keyword-Spotting/resolve/main/vocab.json
291 Bytes
| {"<pad>": 0, "<s>": 1, "</s>": 2, "<unk>": 3, "|": 4, "E": 5, "T": 6, "A": 7, "O": 8, "N": 9, "I": 10, "H": 11, "S": 12, "R": 13, "D": 14, "L": 15, "U": 16, "M": 17, "W": 18, "C": 19, "F": 20, "G": 21, "Y": 22, "P": 23, "B": 24, "V": 25, "K": 26, "'": 27, "X": 28, "J": 29, "Q": 30, "Z": 31} |