Instructions to use wi-lab/lwm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wi-lab/lwm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="wi-lab/lwm")# Load model directly from transformers import LWM model = LWM.from_pretrained("wi-lab/lwm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Sadjad Alikhani commited on
Create config.json
Browse files- config.json +7 -0
config.json
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{
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"architectures": ["LWM"],
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"model_type": "custom",
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"hidden_size": 64, # Replace with your actual model's hidden size (e.g., D_MODEL)
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"num_attention_heads": 12, # Replace with your model's number of attention heads
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"num_hidden_layers": 12 # Replace with your model's number of layers
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}
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