Instructions to use susnato/clvp_dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use susnato/clvp_dev with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="susnato/clvp_dev")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("susnato/clvp_dev") model = AutoModel.from_pretrained("susnato/clvp_dev", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +2 -2
config.json
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"num_attention_heads": 12,
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"num_beam_groups": 1,
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"num_beams": 1,
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"num_hidden_layers":
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"num_return_sequences": 1,
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"output_attentions": false,
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"output_hidden_states": false,
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"num_attention_heads": 12,
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"num_beam_groups": 1,
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"num_beams": 1,
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"num_hidden_layers":
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"num_return_sequences": 1,
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"output_attentions": false,
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"output_hidden_states": false,
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"num_attention_heads": 12,
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"num_beam_groups": 1,
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"num_beams": 1,
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"num_hidden_layers": 20,
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"num_return_sequences": 1,
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"output_attentions": false,
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"output_hidden_states": false,
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"num_attention_heads": 12,
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"num_beam_groups": 1,
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"num_beams": 1,
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"num_hidden_layers": 20,
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"num_return_sequences": 1,
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"output_attentions": false,
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"output_hidden_states": false,
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