Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Marathi
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use simran14/saved_med_model1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simran14/saved_med_model1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="simran14/saved_med_model1")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("simran14/saved_med_model1") model = AutoModelForSpeechSeq2Seq.from_pretrained("simran14/saved_med_model1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from simran14/saved_med_model1: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/simran14/saved_med_model1/resolve/main/training_args.bin
- Command line
-
hf download hf://simran14/saved_med_model1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/simran14/saved_med_model1/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- fe856791b84cfc95fde7e1859428c9ff1a92f3a7004520d27e8160b147b1cef8
- Size of remote file:
- 5.37 kB
- SHA256:
- 342d18bc786fd5daa60d8e684267e801d19daa8f32c9d40276d34d0ff89b2491
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