Instructions to use toolevalxm/SpeechAI-Pro-TestRepo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use toolevalxm/SpeechAI-Pro-TestRepo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="toolevalxm/SpeechAI-Pro-TestRepo")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("toolevalxm/SpeechAI-Pro-TestRepo") model = AutoModelForCTC.from_pretrained("toolevalxm/SpeechAI-Pro-TestRepo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from toolevalxm/SpeechAI-Pro-TestRepo: direct link, hf CLI and curl.
- Browser
- Download file 256 Bytes
-
https://huggingface.co/toolevalxm/SpeechAI-Pro-TestRepo/resolve/main/config.json
- Command line
-
hf download hf://toolevalxm/SpeechAI-Pro-TestRepo/config.json
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curl -L -o config.json https://huggingface.co/toolevalxm/SpeechAI-Pro-TestRepo/resolve/main/config.json
256 Bytes
| { | |
| "model_type": "wav2vec2", | |
| "architectures": [ | |
| "Wav2Vec2ForCTC" | |
| ], | |
| "hidden_size": 768, | |
| "num_hidden_layers": 12, | |
| "num_attention_heads": 12, | |
| "intermediate_size": 3072, | |
| "vocab_size": 32, | |
| "feat_extract_activation": "gelu", | |
| "epoch": 80 | |
| } |