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, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 304 Bytes
2efddce | 1 2 3 4 5 6 7 8 9 10 11 | 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) |