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 checkpoints/latentASR_adapter.pth from voidful/latentASR: direct link, hf CLI and curl.
- Browser
- Download file 10.5 MB
-
https://huggingface.co/voidful/latentASR/resolve/main/checkpoints/latentASR_adapter.pth
- Command line
-
hf download hf://voidful/latentASR/checkpoints/latentASR_adapter.pth
-
curl -L -o latentASR_adapter.pth https://huggingface.co/voidful/latentASR/resolve/main/checkpoints/latentASR_adapter.pth
10.5 MB
- Xet hash:
- 74b5d93c92925e134b960585cc15dd98f37173f72bdd8891770915f806e73354
- Size of remote file:
- 10.5 MB
- SHA256:
- f0ce39fa5e6952fced6992508f3e2b32ea8467442b545678781a0f04e64f2430
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