tessl install tessl/pypi-vllm@0.10.0A high-throughput and memory-efficient inference and serving engine for LLMs
Agent Success
Agent success rate when using this tile
69%
Improvement
Agent success rate improvement when using this tile compared to baseline
1.33x
Baseline
Agent success rate without this tile
52%
Generated
Agent Claude Code
Scenario 1
Synchronous and Asynchronous Engines
Scenario 2
Text Generation and Completion
Scenario 3
Basic Memory Management
Scenario 4
Model Loading and Initialization
Scenario 5
Beam Search and Advanced Sampling
Scenario 6
Sampling Parameters
Scenario 7
LoRA Adapters and Multi-LoRA Support
Scenario 8
Chat-based Generation
Scenario 9
Multi-Modal Support
Scenario 10
Custom Attention Mechanisms