Instructions to use isaacm/wav2vec2-base-timit-eng with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use isaacm/wav2vec2-base-timit-eng with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="isaacm/wav2vec2-base-timit-eng")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("isaacm/wav2vec2-base-timit-eng") model = AutoModelForCTC.from_pretrained("isaacm/wav2vec2-base-timit-eng", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:766e84c66ba262aa51ef224244a3fadf0951db777978e834e6170fcc2bb599f5
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size 377611072
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