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-xlarge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Laudando-Associates-LLC/d-fine-xlarge with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="Laudando-Associates-LLC/d-fine-xlarge", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Laudando-Associates-LLC/d-fine-xlarge", trust_remote_code=True) model = AutoModel.from_pretrained("Laudando-Associates-LLC/d-fine-xlarge", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Laudando-Associates-LLC/d-fine-xlarge: direct link, hf CLI and curl.
- Browser
- Download file 1 GB
-
https://huggingface.co/Laudando-Associates-LLC/d-fine-xlarge/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Laudando-Associates-LLC/d-fine-xlarge/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Laudando-Associates-LLC/d-fine-xlarge/resolve/main/pytorch_model.bin
1 GB
- Xet hash:
- 8ceebf203c41ea660eef1948e1d9311e4eb2239531326ee78656613fe4e2770f
- Size of remote file:
- 1 GB
- SHA256:
- 55f34bedd988453c529b13145424184b80575272858f0c9ce7571f5723457529
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.