Instructions to use opencampus/sign-whisper-german with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use opencampus/sign-whisper-german with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("opencampus/sign-whisper-german", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Christopher H. commited on
Update Readme
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README.md
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@@ -109,9 +109,10 @@ model.freeze_decoder()
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# Define training arguments
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training_args = TrainingArguments(
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num_train_epochs=
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per_device_train_batch_size=256,
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per_device_eval_batch_size=386,
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weight_decay=0.01,
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# Logging settings
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logging_dir="./logs",
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logging_steps=500,
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logging_strategy="steps",
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# Define training arguments
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training_args = TrainingArguments(
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hub_model_id="mrprimenotes/sign-whisper-german_trained",
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push_to_hub=True,
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num_train_epochs=2,
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per_device_train_batch_size=256,
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per_device_eval_batch_size=386,
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weight_decay=0.01,
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# Logging settings
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logging_steps=500,
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logging_strategy="steps",
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