triton-inference-server · nvda-mesharma · Jun 13, 2024 · Jun 8, 2024
diff --git a/README.md b/README.md
@@ -22,104 +22,4 @@ limitations under the License.
 >
 > ##### LATEST RELEASE
 >
-> You are currently on the `main` branch which tracks under-development progress towards the next release. <br>
-> The latest release of the Triton Model Analyzer is 1.40.0 and is available on branch
-> [r24.05](https://github.com/triton-inference-server/model_analyzer/tree/r24.05).
-
-Triton Model Analyzer is a CLI tool which can help you find a more optimal configuration, on a given piece of hardware, for single, multiple, ensemble, or BLS models running on a [Triton Inference Server](https://github.com/triton-inference-server/server/). Model Analyzer will also generate reports to help you better understand the trade-offs of the different configurations along with their compute and memory requirements.
-<br><br>
-
-# Features
-
-### Search Modes
-
-- [Optuna Search](docs/config_search.md#optuna-search-mode) **_-ALPHA RELEASE-_** allows you to search for every parameter that can be specified in the model configuration, using a hyperparameter optimization framework. Please see the [Optuna](https://optuna.org/) website if you are interested in specific details on how the algorithm functions.
-
-- [Quick Search](docs/config_search.md#quick-search-mode) will **sparsely** search the [Max Batch Size](https://github.com/triton-inference-server/server/blob/main/docs/user_guide/model_configuration.md#maximum-batch-size),
-  [Dynamic Batching](https://github.com/triton-inference-server/server/blob/main/docs/user_guide/model_configuration.md#dynamic-batcher), and
-  [Instance Group](https://github.com/triton-inference-server/server/blob/main/docs/user_guide/model_configuration.md#instance-groups) spaces by utilizing a heuristic hill-climbing algorithm to help you quickly find a more optimal configuration
-
-- [Automatic Brute Search](docs/config_search.md#automatic-brute-search) will **exhaustively** search the
-  [Max Batch Size](https://github.com/triton-inference-server/server/blob/main/docs/user_guide/model_configuration.md#maximum-batch-size),
-  [Dynamic Batching](https://github.com/triton-inference-server/server/blob/main/docs/user_guide/model_configuration.md#dynamic-batcher), and
-  [Instance Group](https://github.com/triton-inference-server/server/blob/main/docs/user_guide/model_configuration.md#instance-groups)
-  parameters of your model configuration
-
-- [Manual Brute Search](docs/config_search.md#manual-brute-search) allows you to create manual sweeps for every parameter that can be specified in the model configuration
-
-### Model Types
-
-- [Ensemble Model Search](docs/config_search.md#ensemble-model-search): Model Analyzer can help you find the optimal
-  settings when profiling an ensemble model, utilizing the [Quick Search](docs/config_search.md#quick-search-mode) algorithm
-
-- [BLS Model Search](docs/config_search.md#bls-model-search): Model Analyzer can help you find the optimal
-  settings when profiling a BLS model, utilizing the [Quick Search](docs/config_search.md#quick-search-mode) algorithm
-
-- [Multi-Model Search](docs/config_search.md#multi-model-search-mode): Model Analyzer can help you
-  find the optimal settings when profiling multiple concurrent models, utilizing the [Quick Search](docs/config_search.md#quick-search-mode) algorithm
-
-- [LLM Search](docs/config_search.md#llm-search-mode): Model Analyzer can help you
-  find the optimal settings when profiling large language models, utilizing the [Quick Search](docs/config_search.md#quick-search-mode) algorithm
-
-### Other Features
-
-- [Detailed and summary reports](docs/report.md): Model Analyzer is able to generate
-  summarized and detailed reports that can help you better understand the trade-offs
-  between different model configurations that can be used for your model.
-
-- [QoS Constraints](docs/config.md#constraint): Constraints can help you
-  filter out the Model Analyzer results based on your QoS requirements. For
-  example, you can specify a latency budget to filter out model configurations
-  that do not satisfy the specified latency threshold.
-  <br><br>
-
-# Examples and Tutorials
-
-### **Single Model**
-
-See the [Single Model Quick Start](docs/quick_start.md) for a guide on how to use Model Analyzer to profile, analyze and report on a simple PyTorch model.
-
-### **Multi Model**
-
-See the [Multi-model Quick Start](docs/mm_quick_start.md) for a guide on how to use Model Analyzer to profile, analyze and report on two models running concurrently on the same GPU.
-
-### **Ensemble Model**
-
-See the [Ensemble Model Quick Start](docs/ensemble_quick_start.md) for a guide on how to use Model Analyzer to profile, analyze and report on a simple Ensemble model.
-
-### **BLS Model**
-
-See the [BLS Model Quick Start](docs/bls_quick_start.md) for a guide on how to use Model Analyzer to profile, analyze and report on a simple BLS model.
-<br><br>
-
-# Documentation
-
-- [Installation](docs/install.md)
-- [Model Analyzer CLI](docs/cli.md)
-- [Launch Modes](docs/launch_modes.md)
-- [Configuring Model Analyzer](docs/config.md)
-- [Model Analyzer Metrics](docs/metrics.md)
-- [Model Config Search](docs/config_search.md)
-- [Checkpointing](docs/checkpoints.md)
-- [Model Analyzer Reports](docs/report.md)
-- [Deployment with Kubernetes](docs/kubernetes_deploy.md)
-  <br><br>
-
-# Reporting problems, asking questions
-
-We appreciate any feedback, questions or bug reporting regarding this
-project. When help with code is needed, follow the process outlined in
-the Stack Overflow (https://stackoverflow.com/help/mcve)
-document. Ensure posted examples are:
-
-- minimal – use as little code as possible that still produces the
-  same problem
-
-- complete – provide all parts needed to reproduce the problem. Check
-  if you can strip external dependency and still show the problem. The
-  less time we spend on reproducing problems the more time we have to
-  fix it
-
-- verifiable – test the code you're about to provide to make sure it
-  reproduces the problem. Remove all other problems that are not
-  related to your request/question.
+> You are currently on the `r24.06` branch which tracks under-development progress towards the next release. <br>