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2 changes: 1 addition & 1 deletion .github/workflows/example_tests.yml
Original file line number Diff line number Diff line change
Expand Up @@ -65,7 +65,7 @@ jobs:
matrix:
EXAMPLE: [llm_ptq]
container: &example_container
image: nvcr.io/nvidia/tensorrt-llm/release:1.1.0rc2.post2
image: nvcr.io/nvidia/tensorrt-llm/release:1.2.0rc0.post1
env:
PIP_CONSTRAINT: "" # Disable pip constraint for upgrading packages
HF_TOKEN: ${{ secrets.HF_TOKEN }}
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2 changes: 1 addition & 1 deletion .gitlab/tests.yml
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Expand Up @@ -62,7 +62,7 @@ example-torch:
example-trtllm:
extends: example-torch
timeout: 60m
image: nvcr.io/nvidia/tensorrt-llm/release:1.1.0rc2.post2
image: nvcr.io/nvidia/tensorrt-llm/release:1.2.0rc0.post1
tags: [docker, linux, 2-gpu, sm>=89]
parallel:
matrix:
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1 change: 1 addition & 0 deletions CHANGELOG.rst
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Expand Up @@ -23,6 +23,7 @@ Model Optimizer Changelog (Linux)

**Misc**

- Bump TensorRT-LLM docker to 1.2.0rc0.post1.
- Bump minimum recommended transformers version to 4.53.

0.39 (2025-11-11)
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2 changes: 1 addition & 1 deletion docs/source/getting_started/_installation_for_Linux.rst
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Expand Up @@ -18,7 +18,7 @@ Latest Model Optimizer (``nvidia-modelopt``) currently has the following system
+-------------------------+-----------------------------+
| PyTorch | >=2.6 |
+-------------------------+-----------------------------+
| TensorRT-LLM (Optional) | 1.1.0rc2.post2 |
| TensorRT-LLM (Optional) | 1.2.0rc0.post1 |
+-------------------------+-----------------------------+
| ONNX Runtime (Optional) | 1.22 |
+-------------------------+-----------------------------+
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2 changes: 1 addition & 1 deletion examples/llm_ptq/README.md
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Expand Up @@ -27,7 +27,7 @@ This section focuses on Post-training quantization, a technique that reduces mod

### Docker

For Hugging Face models, please use the TensorRT-LLM docker image (e.g., `nvcr.io/nvidia/tensorrt-llm/release:1.1.0rc2.post2`).
For Hugging Face models, please use the TensorRT-LLM docker image (e.g., `nvcr.io/nvidia/tensorrt-llm/release:1.2.0rc0.post1`).
For NeMo models, use the NeMo container (e.g., `nvcr.io/nvidia/nemo:25.09`).
Visit our [installation docs](https://nvidia.github.io/TensorRT-Model-Optimizer/getting_started/2_installation.html) for more information.

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