Zero-Shot Classification
Transformers
Safetensors
qwen3_5
feature-extraction
decision-model
classification
system-one
multimodal
vision
video
quantized
compressed-tensors
nvfp4
custom_code
8-bit precision
Instructions to use vllm-sr/d3-NVFP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vllm-sr/d3-NVFP4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="vllm-sr/d3-NVFP4", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("vllm-sr/d3-NVFP4", trust_remote_code=True) model = AutoModel.from_pretrained("vllm-sr/d3-NVFP4", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
2 days ago
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Prepare for publishing: current d3_runtime.py, no local paths, drop dev eval files
Verified signature- d3_runtime.py: the version vllm-sr/d3 ships (its release verify skips README and other docs) - QUANT_INFO.json: source and calibration without local paths - eval_summary.json, eval_text_summary.json, eval_vision_summary.json removed (dev subsets the card does not cite) - d3q_engine.py usage line without local paths - README: tags, NVFP4 runtime now on main (#5225), wording - MODEL_MANIFEST.json updated for these files; identity unchanged95a92cc
9 days ago
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NVFP4 (W4A4) quantization of vllm-sr/d3 with FP4 runtime kernels and eval results
Hsiung Li SyunVerified signature61b3f92