Instructions to use KBLab/kb-whisper-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KBLab/kb-whisper-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="KBLab/kb-whisper-large")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("KBLab/kb-whisper-large") model = AutoModelForSpeechSeq2Seq.from_pretrained("KBLab/kb-whisper-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
ggml format for Strict version
#9
by jayant-yadav - opened
I have converted the strict version to GGUF (ggml-model.bin) and uploaded it here : https://huggingface.co/jayant-yadav/ggml-kb-whisper-large_strict
The q5_0 model, however, is still the old one.
jayant-yadav changed discussion title from Ggml format to Strict version to GGUF format to Strict version
It seems to be a GGML version, not GGUF. Or am I missing the download link?
jayant-yadav changed discussion title from GGUF format to Strict version to ggml format for Strict version
That's right. I have renamed it. whisper models are operating on ggml formats and not gguf unlike llamacpp.