Related Issues (20)
- Using custom inference script and models from Hub HOT 1
- get_pipeline function passes Path object rather than PretrainedTokenizer
- No support for multi-GPU HOT 3
- π·οΈ invalid
- Sagemaker endpoint inferencing error with HF model loading from s3bucket with new transformer update HOT 5
- Support multiple return sequences
- HF_TASK Enviournment Variable error HOT 1
- Endpoint creation completes before custom model_fn finishes loading resources
- ARCHITECTURES_2_TASK is limiting the tasks able to be deployed with HF DLC HOT 11
- Make DEFAULT_HF_HUB_MODEL_EXPORT_DIRECTORY configurable
- Sagemaker inference not loading model weight from s3 HOT 2
- Sagemaker endpoint doesn't use GPU (instance ml.g4dn.xlarge) HOT 1
- device kernel image is invalid
- Sagemaker endpoint inference Fails when following a tutorial
- Sagemaker HuggingfaceModel fails on phi3 model deployment HOT 2
- Custom Inference Code - model_fn() takes more positional argument
- Canβt create an inference service for models that depend on packages i.e. `espeak`
- SageMaker fails because Conversation object is not found HOT 3
- How to enable Batch inference on AWS deployed Serverless model from Hub? HOT 1
- Where is the logic for detecting custom inference.py? HOT 6
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from sagemaker-huggingface-inference-toolkit.