Instructions to use dmatekenya/whisper-large-v3-chichewa-variant-b-normalized-transcript with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dmatekenya/whisper-large-v3-chichewa-variant-b-normalized-transcript with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="dmatekenya/whisper-large-v3-chichewa-variant-b-normalized-transcript")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("dmatekenya/whisper-large-v3-chichewa-variant-b-normalized-transcript") model = AutoModelForSpeechSeq2Seq.from_pretrained("dmatekenya/whisper-large-v3-chichewa-variant-b-normalized-transcript", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download whisper-large-v3-chichewa-14h-normalized-transcript/model.safetensors from dmatekenya/whisper-large-v3-chichewa-variant-b-normalized-transcript: direct link, hf CLI and curl.
- Browser
- Download file 6.17 GB
-
https://huggingface.co/dmatekenya/whisper-large-v3-chichewa-variant-b-normalized-transcript/resolve/main/whisper-large-v3-chichewa-14h-normalized-transcript/model.safetensors
- Command line
-
hf download hf://dmatekenya/whisper-large-v3-chichewa-variant-b-normalized-transcript/whisper-large-v3-chichewa-14h-normalized-transcript/model.safetensors
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curl -L -o model.safetensors https://huggingface.co/dmatekenya/whisper-large-v3-chichewa-variant-b-normalized-transcript/resolve/main/whisper-large-v3-chichewa-14h-normalized-transcript/model.safetensors
6.17 GB
- Xet hash:
- 75f18fe0813648af2134aa77c557cd22dd7a653aabb81e3c8977ca3b23fca6d1
- Size of remote file:
- 6.17 GB
- SHA256:
- 24e320f93cb15f71a4280e54d92e1974d7a5784768e6d5f19e86429cb656643e
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