Comments (1)
@UrkoAT Thank you for investigating the root cause. We do notice that there are some bugs in nvgpu which is also in maintenance mode. TS v0.10.0 provides a feature which is able to customize system metrics (see PR)
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Related Issues (20)
- Update LLM/llama2 to Llama3
- Update large_models/inferentia2/llama2 to Llama3
- Update large_models/tp_llama to llama3
- Update large_models/gpt_fast to llama3
- How to pass parameters from preprocessing to postprocessing when using micro-batch operations HOT 4
- Load model failed - error: Worker died HOT 6
- Docker regression failure: test_handler_traceback_logging.py
- Exchange Llama2 against Llama3 in HF_accelerate example
- CUDA out of Memory with low Memory Utilization (CUDA error: device-side assert triggered) HOT 5
- If micro_batch_size of micro-batch is set to 1, then model inference is still batch processing? HOT 1
- question to model inference optimization HOT 1
- Duplicate base_neuronx_continuous_batching_handler.py HOT 1
- Continuous Batching does not work with newest transformer issue
- Limit resource in docker compose and worker in model HOT 2
- model archiver example very long 1 liner
- install dependency via conda
- Enable token authentication as default
- Support "model-control-mode" in configuration
- Make torchserve-kfs docker image multiplatform
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