Automatic Speech Recognition
Transformers
Safetensors
English
asr_model
asr
speech-recognition
speech-to-text
audio
speech-llm
word-timestamps
speaker-diarization
qwen
granite-speech
lora
custom_code
Eval Results (legacy)
Instructions to use mazesmazes/tiny-audio with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mazesmazes/tiny-audio with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mazesmazes/tiny-audio", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForSpeechSeq2Seq model = AutoModelForSpeechSeq2Seq.from_pretrained("mazesmazes/tiny-audio", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from mazesmazes/tiny-audio: direct link, hf CLI and curl.
- Browser
- Download file 20 MB
-
https://huggingface.co/mazesmazes/tiny-audio/resolve/main/tokenizer.json
- Command line
-
hf download hf://mazesmazes/tiny-audio/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/mazesmazes/tiny-audio/resolve/main/tokenizer.json
20 MB
- Xet hash:
- 4b21c9912d656ae3d66b556dd2014b670d5aa14ae4a1711995abc5a3183d9f29
- Size of remote file:
- 20 MB
- SHA256:
- a454aca253aa94d056abd50384d2b15bc468030ad401f9d644b20416b1d46055
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