Automatic Speech Recognition
Transformers
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use kurdai-academy/mms-asr-1b-ckb_Kurdish_Sorani_finetuned_v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kurdai-academy/mms-asr-1b-ckb_Kurdish_Sorani_finetuned_v4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="kurdai-academy/mms-asr-1b-ckb_Kurdish_Sorani_finetuned_v4")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("kurdai-academy/mms-asr-1b-ckb_Kurdish_Sorani_finetuned_v4") model = AutoModelForCTC.from_pretrained("kurdai-academy/mms-asr-1b-ckb_Kurdish_Sorani_finetuned_v4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cf8ed30ca41b57e192287ca63ff7f26270c8b9bac53a4f6e9388c07214158204
- Size of remote file:
- 3.86 GB
- SHA256:
- c19f11cb69264f2133b09778042d59c52236ebebbec157028399094b7d87cbca
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