Comments (4)
Thanks for reporting this! Can reproduce this on my end and will have a look into it.
from serve.
Hi Matthias,
thanks you! Sorry I can't be of any help myself, a total ML newbie.
from serve.
Hi @fredrik-jansson-se
seems like for some reason the operator is not implemented for sparse tensors anymore (It was in the past). Will try to dig deeper into this later. To get you unblocked you can just flip sparse to False here:
from serve.
Awesome, thank you!
from serve.
Related Issues (20)
- 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 HOT 1
- Make torchserve-kfs docker image multiplatform
- Standardize PyTorch 2.x features config in model-config.yaml
- NotImplementedError: Cannot copy out of meta tensor; no data! + Models not generating output text
- The service crashes if the model takes a long time to respond
- Two-way authentication/Mutual SSL in gRPC
- Enable pytest test_example_torch_compile.py:test_example_torch_compile.py
- Enable pytest test_torch_compile.py: test_serve_inference
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