Instructions to use ArthurSynthia/clap1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArthurSynthia/clap1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ArthurSynthia/clap1")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("ArthurSynthia/clap1") model = AutoModel.from_pretrained("ArthurSynthia/clap1") - Notebooks
- Google Colab
- Kaggle
Commit ·
cb288da
1
Parent(s): 081fde1
went back to text_embedding
Browse files- handler.py +2 -2
handler.py
CHANGED
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@@ -26,8 +26,8 @@ class EndpointHandler:
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query = data['inputs']
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text_inputs = self.processor(text=query, return_tensors="pt")
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text_embed = self.model.get_text_features(**text_inputs)[0]
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return requests.get('https://api.ipify.org?format=json').text
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# if 'audio' in data:
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# # Load the audio data into librosa
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query = data['inputs']
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text_inputs = self.processor(text=query, return_tensors="pt")
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text_embed = self.model.get_text_features(**text_inputs)[0]
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return text_embed.detach().numpy()
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# return requests.get('https://api.ipify.org?format=json').text
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# if 'audio' in data:
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# # Load the audio data into librosa
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