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")# 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 mms-1b-all-chichewa-2h/checkpoint-500/scheduler.pt from dmatekenya/whisper-large-v3-chichewa-variant-b-normalized-transcript: direct link, hf CLI and curl.
- Browser
- Download file 1.06 kB
-
https://huggingface.co/dmatekenya/whisper-large-v3-chichewa-variant-b-normalized-transcript/resolve/main/mms-1b-all-chichewa-2h/checkpoint-500/scheduler.pt
- Command line
-
hf download hf://dmatekenya/whisper-large-v3-chichewa-variant-b-normalized-transcript/mms-1b-all-chichewa-2h/checkpoint-500/scheduler.pt
-
curl -L -o scheduler.pt https://huggingface.co/dmatekenya/whisper-large-v3-chichewa-variant-b-normalized-transcript/resolve/main/mms-1b-all-chichewa-2h/checkpoint-500/scheduler.pt
1.06 kB
- Xet hash:
- 28c7b3de33287af41fc338ed69c58344149e89850e1b59eea6355a1a1e8c230b
- Size of remote file:
- 1.06 kB
- SHA256:
- b11eb900cb7af9ecb8797771dfa83159f999b3d7b4f3c5b2ff6e19c51da8de4a
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