feat(pipelines): add evalhub pipelines and small tweaks to existing lora pipelines

components/evaluation/README.md

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 This directory contains components in the **Evaluation** category:
 
+- [Evalhub Kserve](./evalhub_kserve/README.md): Evaluate a model via Eval Hub with a KServe InferenceService.
 - [Lm Eval](./lm_eval/README.md): A Universal LLM Evaluator component using EleutherAI's lm-evaluation-harness.

components/evaluation/evalhub_kserve/OWNERS

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+approvers:
+  - briangallagher
+  - Fiona-Waters
+  - kramaranya
+  - MStokluska
+  - szaher

components/evaluation/evalhub_kserve/README.md

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+# Evalhub Kserve ✨
+
+> ⚠️ **Stability: experimental** — This asset is not yet stable and may change.
+
+## Overview 🧾
+
+Evaluate a model via Eval Hub with a KServe InferenceService.
+
+Creates a KServe ServingRuntime + InferenceService (matching the RHOAI dashboard deployment pattern) to serve the fine-tuned model from the workspace PVC. The InferenceService URL is submitted to Eval Hub for benchmark evaluation. Both resources are cleaned up after completion.
+
+## Inputs 📥
+
+| Parameter | Type | Default | Description |
+| --------- | ---- | ------- | ----------- |
+| `output_metrics` | `dsl.Output[dsl.Metrics]` | `None` | KFP Metrics artifact for evaluation scores. |
+| `output_results` | `dsl.Output[dsl.Artifact]` | `None` | KFP Artifact for full evaluation results JSON. |
+| `evalhub_url` | `str` | `None` | Eval Hub API endpoint (empty = skip evaluation). |
+| `benchmarks` | `list` | `[]` | List of benchmark specs [{"provider_id": "...", "id": "..."}]. |
+| `collection_id` | `str` | `""` | Eval Hub collection ID (alternative to benchmarks list). |
+| `pvc_mount_path` | `str` | `""` | Workspace PVC mount path (triggers KFP PVC mount). |
+| `model_artifact` | `dsl.Input[dsl.Model]` | `None` | Model artifact from upstream training step. |
+| `model_path` | `str` | `None` | Local filesystem path to model directory (if no artifact). |
+| `evalhub_tenant` | `str` | `""` | Eval Hub tenant / namespace header (X-Tenant). |
+| `evalhub_auth_token` | `str` | `""` | Bearer token for Eval Hub auth. |
+| `evalhub_model_name` | `str` | `finetuned-model` | Display name for the model in Eval Hub. |
+| `base_model_name` | `str` | `""` | HF model ID for tokenizer resolution. |
+| `evalhub_job_name` | `str` | `pipeline-eval` | Evaluation job name in Eval Hub. |
+| `evalhub_timeout` | `int` | `7200` | Max seconds to wait for evaluation to complete. |
+| `evalhub_poll_interval` | `int` | `30` | Seconds between eval status polls. |
+| `mlflow_experiment_name` | `str` | `""` | MLflow experiment name (non-empty enables MLflow). |
+| `gpu_count` | `int` | `1` | Number of GPUs for the InferenceService predictor. |
+| `memory` | `str` | `8Gi` | Pod memory request/limit for the predictor (e.g. "8Gi", "32Gi"). |
+| `cpu` | `str` | `2` | CPU request/limit for the predictor (e.g. "2"). |
+| `runtime_image` | `str` | `registry.redhat.io/rhaii/vllm-cuda-rhel9@sha256:ad06abf3bb5235ebb5b2df84cd1b9fd09e823f0ff2eebfc82bb4590275ccfe0b` | Container image for the ServingRuntime (RHOAI vLLM default). |
+| `trust_remote_code` | `bool` | `False` | Pass --trust-remote-code to vLLM (enables arbitrary code from model repos). |
+| `verify_tls` | `bool` | `False` | Verify TLS certificates for Eval Hub API calls (False for self-signed certs). |
+| `isvc_ready_timeout` | `int` | `600` | Max seconds to wait for InferenceService readiness. |
+
+## Metadata 🗂️
+
+- **Name**: evalhub_kserve
+- **Stability**: experimental
+- **Dependencies**:
+  - Kubeflow:
+    - Name: Pipelines, Version: >=2.15.2
+  - External Services:
+    - Name: Eval Hub, Version: >=0.1.0
+    - Name: KServe, Version: >=0.11.0
+    - Name: Kubernetes, Version: >=1.28.0
+    - Name: vLLM (RHOAI), Version: >=0.6.0
+- **Tags**:
+  - evaluation
+  - llm
+  - eval_hub
+  - kserve
+  - benchmarks
+  - metrics
+  - mlflow
+- **Last Verified**: 2026-05-20 00:00:00+00:00
+- **Owners**:
+  - Approvers:
+    - briangallagher
+    - Fiona-Waters
+    - kramaranya
+    - MStokluska
+    - szaher
+
+## Additional Resources 📚
+
+- **Documentation**: [https://github.com/opendatahub-io/eval-hub](https://github.com/opendatahub-io/eval-hub)

components/evaluation/evalhub_kserve/__init__.py

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+"""Eval Hub Evaluation Component — KServe variant.
+
+This component provides model evaluation via the Eval Hub service,
+using a KServe InferenceService + ServingRuntime for model serving
+(matching the RHOAI dashboard deployment pattern).
+"""
+
+from .component import evalhub_evaluator_kserve
+
+__all__ = ["evalhub_evaluator_kserve"]