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-flash with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vllm-sr/d3-flash with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="vllm-sr/d3-flash", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("vllm-sr/d3-flash", trust_remote_code=True) model = AutoModel.from_pretrained("vllm-sr/d3-flash", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download assets/banner.png from vllm-sr/d3-flash: direct link, hf CLI and curl.
- Browser
- Download file 2.23 MB
-
https://huggingface.co/vllm-sr/d3-flash/resolve/main/assets/banner.png
- Command line
-
hf download hf://vllm-sr/d3-flash/assets/banner.png
-
curl -L -o banner.png https://huggingface.co/vllm-sr/d3-flash/resolve/main/assets/banner.png
2.23 MB

- Xet hash:
- ccb4990f1b53a478f5350fc72ad3f669d408fc6e33f3acc63a770fd7e8acd9ba
- Size of remote file:
- 2.23 MB
- SHA256:
- d621431eb5d1b20650a35a2e27c30f372631592cabff260679f12be9813eebc5
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