Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
Malayalam
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use kavyamanohar/whisper-small-malayalam with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kavyamanohar/whisper-small-malayalam with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="kavyamanohar/whisper-small-malayalam")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("kavyamanohar/whisper-small-malayalam") model = AutoModelForSpeechSeq2Seq.from_pretrained("kavyamanohar/whisper-small-malayalam", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from kavyamanohar/whisper-small-malayalam: direct link, hf CLI and curl.
- Browser
- Download file 967 MB
-
https://huggingface.co/kavyamanohar/whisper-small-malayalam/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://kavyamanohar/whisper-small-malayalam/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/kavyamanohar/whisper-small-malayalam/resolve/main/pytorch_model.bin
967 MB
- Xet hash:
- 46cf7a2a7a5b4fb22530c9bc8552a70c016b0f22e049cf4b6db006873b158a0a
- Size of remote file:
- 967 MB
- SHA256:
- 88b4e6fd56edb66d3dfaf523c28f1be79f265c44a482898d1294ebb1e2a00a7f
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