Automatic Speech Recognition
Transformers
qwen3-asr
latent-reasoning
test-time-compute
parameter-efficient
Instructions to use voidful/latentASR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use voidful/latentASR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="voidful/latentASR")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("voidful/latentASR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download .gitignore from voidful/latentASR: direct link, hf CLI and curl.
- Browser
- Download file 279 Bytes
-
https://huggingface.co/voidful/latentASR/resolve/main/.gitignore
- Command line
-
hf download hf://voidful/latentASR/.gitignore
-
curl -L -o .gitignore https://huggingface.co/voidful/latentASR/resolve/main/.gitignore
279 Bytes
| __pycache__/ | |
| *.py[cod] | |
| .pytest_cache/ | |
| .ruff_cache/ | |
| .mypy_cache/ | |
| .venv/ | |
| venv/ | |
| env/ | |
| logs/ | |
| eval_runs/ | |
| wandb/ | |
| *.log | |
| core | |
| *.tmp | |
| # Keep the released adapter checkpoint, ignore accidental large local artifacts. | |
| *.bin | |
| *.safetensors | |
| *.ckpt | |
| *.pt | |
| *.pth | |
| !checkpoints/latentASR_adapter.pth | |