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
print shape of used embeddings
Browse files
model.py
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@@ -1163,6 +1163,7 @@ class WhisperEncoder(WhisperPreTrainedModel):
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# CUSTOM
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position_embeddings = self.get_position_embeddings(sequence_length)
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hidden_states = inputs_embeds + position_embeddings
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# CUSTOM
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position_embeddings = self.get_position_embeddings(sequence_length)
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print(f"Position_embeddings shape: {position_embeddings.shape}")
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hidden_states = inputs_embeds + position_embeddings
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