Comments (2)
philschmid
commented on June 12, 2024
Hey, the sagemaker-hugginface-inference-toolkit is mainly used in the Hugging Face Deep Learning Container. Where mms (multi-model-server) installed separately: https://github.com/aws/deep-learning-containers/blob/1fd68dd26f5ef31da2ed6576378ae6c729808848/huggingface/pytorch/inference/docker/1.9/py3/Dockerfile.cpu#L90
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BastianZim
commented on June 12, 2024
Ahh ok, thanks for the clarification!
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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 2
- 🏷️ 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
- Sagemaker endpoint doesn't use GPU (instance ml.g4dn.xlarge) HOT 1
- How to access CustomAttributes in async inferece request input_fn HOT 1
- [DOCS] List of available HF_TASK and default inference scripts HOT 4
- Dead Link for Available HF_Tasks HOT 1
- SageMaker deployment errors HOT 2
- Error on Sagemaker deployment for v1.0.1 HOT 1
- How can I delpoy a model with AWS S3 and without downloading model from hunggingface via TGI image on Sagemaker? HOT 2
- 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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