Zero-Shot Classification
Transformers
Safetensors
qwen3_5
feature-extraction
decision-model
classification
system-one
multimodal
vision
video
quantized
compressed-tensors
fp8
custom_code
Eval Results
Instructions to use vllm-sr/d3-FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vllm-sr/d3-FP8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="vllm-sr/d3-FP8", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("vllm-sr/d3-FP8", trust_remote_code=True) model = AutoModel.from_pretrained("vllm-sr/d3-FP8", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Card: the revision to serve
Browse files
README.md
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[vllm-project/semantic-router#5066](https://github.com/vllm-project/semantic-router/pull/5066) adds FP8 and int4 Decision 3.0 packages to the [vLLM Semantic Router](https://github.com/vllm-project/semantic-router) model runtime. Until it is merged and released, the model runtime from that pull request serves this checkpoint:
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```bash
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vllm-srun serve vllm-sr/d3-FP8 --revision
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```
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```bash
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[vllm-project/semantic-router#5066](https://github.com/vllm-project/semantic-router/pull/5066) adds FP8 and int4 Decision 3.0 packages to the [vLLM Semantic Router](https://github.com/vllm-project/semantic-router) model runtime. Until it is merged and released, the model runtime from that pull request serves this checkpoint:
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```bash
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vllm-srun serve vllm-sr/d3-FP8 --revision 94c520d306f0150df84c40e55071b315d9b4dec9 --device rocm:0 --port 8100
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```
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```bash
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