Automatic Speech Recognition
Transformers
ONNX
PEFT
whisper
polywhisper
indic-asr
hindi-asr
tamil-speech-recognition
telugu-stt
bengali-asr
marathi-speech-to-text
speech-recognition
multilingual
lora
hindi
tamil
telugu
bengali
marathi
indic-languages
indian-languages
speech-to-text
low-resource-asr
fleurs
indicvoices
quantized
efficient-asr
edge-asr
Eval Results (legacy)
Instructions to use eulogik/polywhisper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eulogik/polywhisper with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="eulogik/polywhisper")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("eulogik/polywhisper") model = AutoModelForSpeechSeq2Seq.from_pretrained("eulogik/polywhisper", device_map="auto") - PEFT
How to use eulogik/polywhisper with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Download baselines_summary_medium.json from eulogik/polywhisper: direct link, hf CLI and curl.
- Browser
- Download file 67 Bytes
-
https://huggingface.co/eulogik/polywhisper/resolve/main/baselines_summary_medium.json
- Command line
-
hf download hf://eulogik/polywhisper/baselines_summary_medium.json
-
curl -L -o baselines_summary_medium.json https://huggingface.co/eulogik/polywhisper/resolve/main/baselines_summary_medium.json
67 Bytes
| { | |
| "mr": { | |
| "wer": 98.18, | |
| "cer": 51.43, | |
| "n": 1015 | |
| } | |
| } |