Automatic Speech Recognition
Transformers
Safetensors
Hindi
English
qwen3_asr
speech
speech-to-text
hindi-asr
hindi-speech-to-text
hinglish-asr
voice-agents
streaming-asr
hindi
code-switching
hinglish
maya-research
qwen3-asr
Eval Results (legacy)
Instructions to use maya-research/maya-transcribe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use maya-research/maya-transcribe with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="maya-research/maya-transcribe")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("maya-research/maya-transcribe") model = AutoModelForMultimodalLM.from_pretrained("maya-research/maya-transcribe", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from maya-research/maya-transcribe: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/maya-research/maya-transcribe/resolve/main/tokenizer.json
- Command line
-
hf download hf://maya-research/maya-transcribe/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/maya-research/maya-transcribe/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 0784dd4c4858bb0fc0e2c0745a31ee688eb178cc7a900fc7039a0d31fff0a024
- Size of remote file:
- 11.4 MB
- SHA256:
- fe1fad59be22a41ee293363fcf95fdedbc7c93f3b49270b1d2e18bd1399a7a05
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