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, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 417 Bytes
c580b09 55413d4 c580b09 55413d4 c580b09 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | import torch
from transformers import (WEIGHTS_NAME, CONFIG_NAME, AutoConfig)
from model import (TestConfig, TestModel)
if __name__ == "__main__":
config = TestConfig()
model = TestModel(config)
x = torch.rand(16,4)
pred = model(x)
print(pred)
AutoConfig.register("test-model", TestConfig)
config.save_pretrained(CONFIG_NAME)
model.save_pretrained(WEIGHTS_NAME) |