Instructions to use ThomasFG/67.5-67.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThomasFG/67.5-67.5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ThomasFG/67.5-67.5")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ThomasFG/67.5-67.5") model = AutoModelForSpeechSeq2Seq.from_pretrained("ThomasFG/67.5-67.5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- af0354200f113c5130dcbd569ad65400ffea0624765e7114cd0cb54c62e74cba
- Size of remote file:
- 967 MB
- SHA256:
- cf43ba7ebba402c65dc3ba761cc226d3274da4c473ba46e90dc53361f1f1bf0e
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