Instructions to use supawichwac/training with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use supawichwac/training with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="supawichwac/training")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("supawichwac/training") model = AutoModelForSpeechSeq2Seq.from_pretrained("supawichwac/training") - Notebooks
- Google Colab
- Kaggle
Saving train state of step 100
Browse files- checkpoint-100-epoch-0/model.safetensors +3 -0
- checkpoint-100-epoch-0/model_1.safetensors +3 -0
- checkpoint-100-epoch-0/optimizer.bin +3 -0
- checkpoint-100-epoch-0/random_states_0.pkl +3 -0
- checkpoint-100-epoch-0/scheduler.bin +3 -0
- distil-whisper/events.out.tfevents.1715051868.server02.1327224.0 +2 -2
checkpoint-100-epoch-0/model.safetensors
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oid sha256:a659856d3de6c69e8532aa6658438fa9568a940f6dc08307839ac0c7820ceed2
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size 3025686376
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checkpoint-100-epoch-0/model_1.safetensors
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oid sha256:6b395c8a7e2bda655c415580106288d0387c227efd641bf4e11c1cd735fdb37a
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size 4361070048
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checkpoint-100-epoch-0/optimizer.bin
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oid sha256:a807a16f17f4ded5c7d0fd15e650a1d75afc3d26970802a5de1788217552e2d9
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size 955539578
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checkpoint-100-epoch-0/random_states_0.pkl
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oid sha256:1a7236bbe98c87be8a0735207aaa4e340e29acce176e1624ae6c5f0bf53941fd
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size 14344
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checkpoint-100-epoch-0/scheduler.bin
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oid sha256:d1fb12e131d1377879ac9b0a15c30a531e9ff47fc8821ee05539954e1d56fbe7
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size 1064
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distil-whisper/events.out.tfevents.1715051868.server02.1327224.0
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oid sha256:80fb8c364619dac5705f428dce067cd2b6527af3b25c877f335fcdcb52a2e78f
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size 1304
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