Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Persian
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use SadeghK/whisper-large-v3-turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SadeghK/whisper-large-v3-turbo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="SadeghK/whisper-large-v3-turbo")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("SadeghK/whisper-large-v3-turbo") model = AutoModelForSpeechSeq2Seq.from_pretrained("SadeghK/whisper-large-v3-turbo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download ggml-large-v3-turbo-fa.bin from SadeghK/whisper-large-v3-turbo: direct link, hf CLI and curl.
- Browser
- Download file 1.62 GB
-
https://huggingface.co/SadeghK/whisper-large-v3-turbo/resolve/5687fdf8bb77414b2844cf6475893b840ecbc7f2/ggml-large-v3-turbo-fa.bin
- Command line
-
hf download hf://SadeghK/whisper-large-v3-turbo@5687fdf8bb77414b2844cf6475893b840ecbc7f2/ggml-large-v3-turbo-fa.bin
-
curl -L -o ggml-large-v3-turbo-fa.bin https://huggingface.co/SadeghK/whisper-large-v3-turbo/resolve/5687fdf8bb77414b2844cf6475893b840ecbc7f2/ggml-large-v3-turbo-fa.bin
1.62 GB
- Xet hash:
- 7ebe30856609ee06e81022230bf1b2442cafd9a086ae3e7e5aabe7ac8e0c3fff
- Size of remote file:
- 1.62 GB
- SHA256:
- 60cac5d4be4552ae806de48ba57c39bad4a3c732f9866a77d80e90104db3a870
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