Instructions to use goea/whisper-small-sagemaker-test.en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use goea/whisper-small-sagemaker-test.en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="goea/whisper-small-sagemaker-test.en")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("goea/whisper-small-sagemaker-test.en") model = AutoModelForSpeechSeq2Seq.from_pretrained("goea/whisper-small-sagemaker-test.en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
s3://sagemaker-whisper-testing/output/small/en/sagemaker-whispertra-250720-0906-009-f5805b99/output/model.tar.gz
Browse files- config.json +1 -1
- model.safetensors +1 -1
config.json
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"decoder_layerdrop": 0.0,
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"decoder_layers": 12,
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"decoder_start_token_id": 50257,
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"dropout": 0.
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"encoder_attention_heads": 12,
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"encoder_ffn_dim": 3072,
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"encoder_layerdrop": 0.0,
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"decoder_layerdrop": 0.0,
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"decoder_layers": 12,
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"decoder_start_token_id": 50257,
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"dropout": 0.009512140416329425,
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"encoder_attention_heads": 12,
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"encoder_ffn_dim": 3072,
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"encoder_layerdrop": 0.0,
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 967001224
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