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This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
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done- https://github.com/bentoml/BentoML/blob/master/DEVELOPMENT.md
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Related Issues (20)
- bug: asyncio.exceptions.CancelledError HOT 4
- On-demand loading with limited GPU resource
- bug: BentoML Ray ray.serve._private.storage.kv_store.KVStoreError: 8 HOT 1
- feature: not able to install packages from private PyPI easily HOT 3
- bug: not able to mount secret
- bug: Compiled functions can't take variable number of arguments or use keyword-only arguments with defaults HOT 1
- bug: BentoML installation throwing mutable default <class 'bentoml.types.HTTPHeaders'> for field headers is not allowed: use default_factory HOT 2
- bug: bentoml.transformers.save_model() is constrained on image-classification? HOT 1
- bug: adaptive batching not work in mlflow model (gensim word2vec)
- bug: aiohttp.client_exceptions.ClientResponseError "Header value is too long"
- bug: Error calling zero-argument runner method
- bug: fail to build bento on none-gpu env. because NvidiaGpuResource.from_system throws HOT 1
- feature: make sync_with_hub_version optional HOT 2
- bug: cannot use local path as model_id
- feature: video/audio IO descriptors HOT 2
- enhancement: Include the trace_id, span_id, and service name in the monitoring log
- bug: TransformersRunnable.__init__ sets torch default tensor type to torch.cuda.FloatTensor even if gpu is not available
- feature: Allow "backupCount" to be specified in environment variable for the default monitoring log's TimedRotatingFileHandler HOT 1
- bentoml.onnx.get is not working after onnx conversion is completed
- bug: X-Amzn-SageMaker-Custom-Attributes header conflict prevents custom value for Sagemaker endpoint
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