Instructions to use ImanN1/finetune_wav2vec2_960h_thirty with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ImanN1/finetune_wav2vec2_960h_thirty with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ImanN1/finetune_wav2vec2_960h_thirty")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("ImanN1/finetune_wav2vec2_960h_thirty") model = AutoModelForCTC.from_pretrained("ImanN1/finetune_wav2vec2_960h_thirty", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from ImanN1/finetune_wav2vec2_960h_thirty: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/ImanN1/finetune_wav2vec2_960h_thirty/resolve/main/model.safetensors
- Command line
-
hf download hf://ImanN1/finetune_wav2vec2_960h_thirty/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/ImanN1/finetune_wav2vec2_960h_thirty/resolve/main/model.safetensors
378 MB
- Xet hash:
- 682f2b7c137ef0362d85a91d81ab770579fbbc8c50cc3795eac934ce71e9b3a2
- Size of remote file:
- 378 MB
- SHA256:
- c5bd5a0f94341bb0f793d336f1a01acd40f548a1bd9178a685813bfdf84ded2a
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