Instructions to use lysandre/test_dynamic_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lysandre/test_dynamic_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="lysandre/test_dynamic_model", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("lysandre/test_dynamic_model", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| import torch | |
| from transformers import BertModel | |
| from .configuration import NewModelConfig | |
| class NewModel(BertModel): | |
| config_class = NewModelConfig | |
| def __init__(self, config): | |
| super().__init__(config) | |
| self.last_layer = torch.nn.Linear(config.hidden_size, config.new_hidden_size) |