Object Detection
PyTorch
TensorBoard
ONNX
Safetensors
Transformers
English
d_fine
feature-extraction
AgTech
custom_code
Eval Results (legacy)
Instructions to use Laudando-Associates-LLC/d-fine-nano with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Laudando-Associates-LLC/d-fine-nano with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="Laudando-Associates-LLC/d-fine-nano", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Laudando-Associates-LLC/d-fine-nano", trust_remote_code=True) model = AutoModel.from_pretrained("Laudando-Associates-LLC/d-fine-nano", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2b6d96353ee9f529d9cc51903c72f832d83de4e8a2f8ff0c02a78317cea3d8f5
- Size of remote file:
- 60.8 MB
- SHA256:
- 664ac0d39476e1bcdffd409750462ef2ff9f9f0a6029c45531bc926f096821ed
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