Make wheel build manual CI job and diffusers test fix (#529)

- Allow wheel build and release manual without depending on test status
(sometimes nmm-sandbox tests fail because of unavailable slurm machines)

Signed-off-by: Keval Morabia <[email protected]>

Author: kevalmorabia97

.gitlab/release.yml

@@ -5,17 +5,20 @@ build-and-upload-wheels:
   stage: release
   timeout: 15m
   tags: [type/docker, os/linux] # Use a runner with these tags
+  needs: []
   rules:
     - if: $JET_ONLY != null
       when: never
     - if: $CI_COMMIT_TAG =~ /^\d+\.\d+\.\d+$/
+      when: manual
       variables:
         RELEASE: "true"
         TWINE_USERNAME: svc-dl-algo-ammo
         TWINE_PASSWORD: $ARTIFACTORY_TOKEN # Configured in GitLab > Settings > CI/CD
         REPO_URL: https://urm.nvidia.com/artifactory/api/pypi/sw-dl-algo-ammo-pypi-local
     - if: $CI_PIPELINE_SOURCE == "schedule"
       variables:
+        when: manual
         RELEASE: "false"
         TWINE_USERNAME: gitlab-ci-token
         TWINE_PASSWORD: $CI_JOB_TOKEN

CHANGELOG.rst

@@ -1,13 +1,5 @@
 Model Optimizer Changelog (Linux)
 =================================
-0.41 (2025-12-xx)
-^^^^^^^^^^^^^^^^^
-
-**Deprecations**
-
-**New Features**
-- Add FP8/NVFP4 KV cache quantization support for Megatron Core models.
-
 
 0.40 (2025-12-xx)
 ^^^^^^^^^^^^^^^^^
@@ -20,8 +12,9 @@ Model Optimizer Changelog (Linux)
 
 - Add MoE (e.g. Qwen3-30B-A3B) pruning support for ``num_moe_experts``, ``moe_ffn_hidden_size`` and ``moe_shared_expert_intermediate_size`` parameters in Minitron pruning (``mcore_minitron``).
 - Add ``specdec_bench`` example to benchmark speculative decoding performance. See `examples/specdec_bench/README.md <https://github.com/NVIDIA/TensorRT-Model-Optimizer/tree/main/examples/specdec_bench#speculative-decoding-benchmark>`_ for more details.
+- Add FP8/NVFP4 KV cache quantization support for Megatron Core models.
 
-0.39 (2025-11-14)
+0.39 (2025-11-11)
 ^^^^^^^^^^^^^^^^^
 
 **Deprecations**