Zero-Shot Classification
Transformers
Safetensors
qwen3_5
feature-extraction
decision-model
classification
system-one
multimodal
vision
video
custom_code
Eval Results
Instructions to use vllm-sr/d3-nano with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vllm-sr/d3-nano with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="vllm-sr/d3-nano", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("vllm-sr/d3-nano", trust_remote_code=True) model = AutoModel.from_pretrained("vllm-sr/d3-nano", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download assets/index-pareto.png from vllm-sr/d3-nano: direct link, hf CLI and curl.
- Browser
- Download file 209 kB
-
https://huggingface.co/vllm-sr/d3-nano/resolve/main/assets/index-pareto.png
- Command line
-
hf download hf://vllm-sr/d3-nano/assets/index-pareto.png
-
curl -L -o index-pareto.png https://huggingface.co/vllm-sr/d3-nano/resolve/main/assets/index-pareto.png
209 kB

- Xet hash:
- 179696e837104bba8414ec1bdf7b6b800a8d67a946dbc767680d694752db03ce
- Size of remote file:
- 209 kB
- SHA256:
- 8d25fac5642a911ca203f5d3af706391fe33503dd54a719df38e21c923ac48ba
·
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