Instructions to use copper-light/test-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use copper-light/test-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="copper-light/test-model", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("copper-light/test-model", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
e61ab3d
1
Parent(s): f35de06
update
Browse files
pytorch_model.bin/config.json → config.json
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pytorch_model.bin/model.py
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from transformers import PreTrainedModel, PretrainedConfig
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from torch import nn
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class TestConfig(PretrainedConfig):
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model_type = "test-model"
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def __init__(self, input_dim=4, output_dim=16, **kwargs):
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self.input_dim = input_dim
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self.output_dim = output_dim
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super().__init__(**kwargs)
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class TestModel(PreTrainedModel):
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config_class = TestConfig
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def __init__(self, config):
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super().__init__(config)
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self.layer = nn.Linear(config.input_dim, config.output_dim)
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def forward(self, input):
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return self.layer(input)
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