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Trying to run sample on two devices (Pixel 8 Android 15 with "Enable on-device GenAI Features" enabled, Pixel 9 Pro w/ GrapheneOS w/play services & AICore installed), and I get the following error:
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### Description
The _inference service uses the _ml/trained_models API to deploy models for use in the inference service. However, users are still able to manage these deployments using the trained…
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### Problem Statement
Nowadays remote model servers like AWS SageMaker, BedRock, or OpenAI, Cohere, etc all support batch predict APIs, which allow users to send large amount of synchronous request…
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### Issues Policy acknowledgement
- [X] I have read and agree to submit bug reports in accordance with the [issues policy](https://www.github.com/mlflow/mlflow/blob/master/ISSUE_POLICY.md)
### Where…
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Create an API service that can be called to process the requests from the app.
We can then host this into a server.
The API shall accept the role and the token.
Instructions for deploying the …
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### Elasticsearch Version
8.14.0-SNAPSHOT
### Installed Plugins
_No response_
### Java Version
JBR-17.0.9+8-1166.2-nomod
### OS Version
23.3.0 Darwin Kernel Version 23.3.0: Wed De…
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**Describe the bug**
When running as a non-root user within a container, sagemaker-inference fails to start the multi-model-server. This works when all packages are installed as root, and the entry…
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### Description
The inference API supports text embedding and rerank task types. If a inference endpoint is created for text embedding, and a request is made to perform inference and the request co…
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### 🚀 The feature
## Author: Li Ning
## Background
A stateful model possesses the ability to detect interdependencies between successive inference requests. This type of model maintains a persist…
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/kind bug
**What steps did you take and what happened:**
Deployed inferenceservice iris-classifier-deployment:
```
% kubectl get inferenceservices
NAME URL …