Comments (6)
Hello!
I'm interested in helping out with this. That said, what's the main blocker on implementing support for GPU MME?
Why wouldn't it suffice to just add the multi-models
tag?
from sagemaker-huggingface-inference-toolkit.
Yes, the HuggingFace Inference Toolkit uses similar mechanism than the other ones. You can find documentation here:
- https://docs.aws.amazon.com/sagemaker/latest/dg/create-multi-model-endpoint.html
- https://sagemaker.readthedocs.io/en/stable/api/inference/multi_data_model.html
from sagemaker-huggingface-inference-toolkit.
Hi @philschmi,
thanks for the resources !!
in this https://www.philschmid.de/sagemaker-huggingface-multi-container-endpoint you mention that multi-container endpoints are not possible on GPU ??
is this true for multi-modal endpoint also ??
from sagemaker-huggingface-inference-toolkit.
Yes, currently Multi-Model Endpoint also only works with CPU instances
from sagemaker-huggingface-inference-toolkit.
thanks @philschmid you saved me sometime
from sagemaker-huggingface-inference-toolkit.
Second this question. It has been 1.5 years since the original question, yet is GPU still not supported?
from sagemaker-huggingface-inference-toolkit.
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 5
- Support load_lora_weights in inference API deploy
- Where is the logic for detecting custom inference.py? HOT 6
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