Remove requirements and performance tips sections from README.md for clarity and conciseness.

README.md

@@ -100,29 +100,6 @@ hf jobs uv run \
     --max-model-len 8000
 ```
 
-## 🎯 Requirements
-
-All scripts in this collection require:
-
-- **NVIDIA GPU** with CUDA support
-- **Python 3.10+**
-- **UV package manager** ([install UV](https://docs.astral.sh/uv/getting-started/installation/))
-
-## 🚀 Performance Tips
-
-### GPU Selection
-
-- **L4 GPU** (`--flavor l4x1`): Best value for classification and smaller models
-- **L4x4** (`--flavor l4x4`): Multi-GPU setup for large models (30B+ parameters)
-- **A10 GPU** (`--flavor a10g-large`): Higher memory for larger models
-- **A100** (`--flavor a100-large`): Maximum performance for demanding workloads
-- Adjust batch size and tensor parallelism based on GPU configuration
-
-### Batch Sizes
-
-- **Classification**: Start with 10,000 locally, up to 100,000 on HF Jobs
-- **Generation**: vLLM handles batching automatically - no manual configuration needed
-
 ### Multi-GPU Tensor Parallelism
 
 - Auto-detects available GPUs by default
@@ -193,15 +170,6 @@ This image includes:
 - `UV_PRERELEASE=if-necessary`: Allow pre-release packages when required
 - `HF_HUB_ENABLE_HF_TRANSFER=1`: Automatically enabled for faster downloads
 
-## 📝 Contributing
-
-Have a vLLM script to share? We welcome contributions that:
-
-- Solve real inference problems
-- Include clear documentation
-- Follow UV script best practices
-- Include HF Jobs examples
-
 ## 🔗 Resources
 
 - [vLLM Documentation](https://docs.vllm.ai/)