Request for More Efficient Vision Encoder Backbone
Feature request to add EUPE vision encoder as a more efficient pretrained backbone option for RF-DETR object detection model.
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Similar Problems
surfaced semanticallyTransformers Library Missing EfficientViT-SAM Model Support
The Hugging Face Transformers library does not include EfficientViT-SAM, a lighter and faster alternative to ViT-based SAM for interactive image segmentation. Users must integrate it manually outside the standard Transformers ecosystem.
llama.cpp lacks native support for 1-bit quantized Bonsai LLM models
The new 1-bit Bonsai 8B model achieves competitive performance at 14x smaller size, but requires a fork of llama.cpp to run. Users want native support in the main project to enable efficient local inference with this architecture.
Vision Encoder Resolution Extension via Interpolation
Feature request to extend vision model resolution by interpolating patch position embeddings, enabling higher-res input without architecture changes.
VLM Model Wrapper Lacks Piecewise CUDAGraph Support
Piecewise cudagraph is not supported for VLM model wrappers in the auto-deploy pipeline. Users deploying vision-language models like Qwen3.5 cannot leverage cudagraph optimizations for the text model component.
LoRA Support Missing for Gemma 4 Models in vLLM
vLLM added Gemma 4 model support but LoRA adapters do not work for Gemma4ForCausalLM or Gemma4ForConditionalGeneration, blocking fine-tuned model deployment.
Problem descriptions, scores, analysis, and solution blueprints may be updated as new community data becomes available.