Zero-Shot Classification
Transformers
Safetensors
qwen3_5
feature-extraction
decision-model
classification
system-one
multimodal
vision
video
custom_code
Instructions to use vllm-sr/d3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vllm-sr/d3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="vllm-sr/d3", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("vllm-sr/d3", trust_remote_code=True) model = AutoModel.from_pretrained("vllm-sr/d3", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download assets/index-pareto.png from vllm-sr/d3: direct link, hf CLI and curl.
- Browser
- Download file 208 kB
-
https://huggingface.co/vllm-sr/d3/resolve/main/assets/index-pareto.png
- Command line
-
hf download hf://vllm-sr/d3/assets/index-pareto.png
-
curl -L -o index-pareto.png https://huggingface.co/vllm-sr/d3/resolve/main/assets/index-pareto.png
208 kB

- Xet hash:
- 9d3371d41c84c1006bc6d2cbd4a4fb7a5976940c91e450f3b03bf229e71ef932
- Size of remote file:
- 208 kB
- SHA256:
- 22827a6293301dd024791678d6cd7d6d3d6d9352bd9422b591c443e9d08afacb
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