Automatic Speech Recognition
Transformers
Safetensors
Tajik
whisper
hf-asr-leaderboard
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use muhtasham/whisper-tg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use muhtasham/whisper-tg with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="muhtasham/whisper-tg")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("muhtasham/whisper-tg") model = AutoModelForSpeechSeq2Seq.from_pretrained("muhtasham/whisper-tg", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from muhtasham/whisper-tg: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/muhtasham/whisper-tg/resolve/main/training_args.bin
- Command line
-
hf download hf://muhtasham/whisper-tg/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/muhtasham/whisper-tg/resolve/main/training_args.bin
5.5 kB
- Xet hash:
- 25b78999e3919cbf22c1a6aa5a9e64974abb805ed56c16353d4b3ebf6a062b5a
- Size of remote file:
- 5.5 kB
- SHA256:
- d40151174c66ef2df37c94565a4c04ccf600abec8b0bde92424152c96dcc4840
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