Improve supported provider models #9101
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Signed-off-by: harupy <[email protected]>
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| @@ -244,61 +244,18 @@ The table below presents a non-exhaustive list of models and a corresponding rou | |||
| With the rapid development of LLMs, there is no guarantee that this list will be up to date at all times. However, the associations listed | |||
| below can be used as a helpful guide when configuring a given route for any newly released model types as they become available with a given provider. | |||
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Can we add some text that lets a reader know that the N/A values actually mean that the provider currently doesn't support this interface?
At a quick cursory glance at the table it's hard to know if the N/A is a placeholder that we just didn't fill in or that it's actually an unavailable route configuration.
Signed-off-by: harupy <[email protected]>
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Signed-off-by: harupy <[email protected]>
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Signed-off-by: harupy <[email protected]>
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Related Issues/PRs
#xxxWhat changes are proposed in this pull request?
Improve supported provider models.
Before
After
How is this patch tested?
Does this PR change the documentation?
Release Notes
Is this a user-facing change?
(Details in 1-2 sentences. You can just refer to another PR with a description if this PR is part of a larger change.)
What component(s), interfaces, languages, and integrations does this PR affect?
Components
area/artifacts: Artifact stores and artifact loggingarea/build: Build and test infrastructure for MLflowarea/docs: MLflow documentation pagesarea/examples: Example codearea/gateway: AI Gateway service, Gateway client APIs, third-party Gateway integrationsarea/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registryarea/models: MLmodel format, model serialization/deserialization, flavorsarea/recipes: Recipes, Recipe APIs, Recipe configs, Recipe Templatesarea/projects: MLproject format, project running backendsarea/scoring: MLflow Model server, model deployment tools, Spark UDFsarea/server-infra: MLflow Tracking server backendarea/tracking: Tracking Service, tracking client APIs, autologgingInterface
area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev serverarea/docker: Docker use across MLflow's components, such as MLflow Projects and MLflow Modelsarea/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registryarea/windows: Windows supportLanguage
language/r: R APIs and clientslanguage/java: Java APIs and clientslanguage/new: Proposals for new client languagesIntegrations
integrations/azure: Azure and Azure ML integrationsintegrations/sagemaker: SageMaker integrationsintegrations/databricks: Databricks integrationsHow should the PR be classified in the release notes? Choose one:
rn/breaking-change- The PR will be mentioned in the "Breaking Changes" sectionrn/none- No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" sectionrn/feature- A new user-facing feature worth mentioning in the release notesrn/bug-fix- A user-facing bug fix worth mentioning in the release notesrn/documentation- A user-facing documentation change worth mentioning in the release notes