rights reserved. Presenter: Haichen Shen, Yao Wang Amazon SageMaker Neo, Deep Engine Science Dynamic Model in TVM AWS AI© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Models with models© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Support dynamic model in TVM ● Support Any-dim in typing ● Use shape function to compute the type at runtime ● Virtual input_name = "data" input_shape = [tvm.relay.Any(), 3, 224, 224] dtype = "float32" block = get_model('resnet50_v1', pretrained=True) mod, params = relay.frontend.from_mxnet(block, shape={input_name:

Efficient Mixture-of-Experts Language Model DeepSeek-AI research@deepseek.com Abstract We present DeepSeek-V2, a strong Mixture-of-Experts (MoE) language model characterized by economical training and DeepSeek-V2 and its chat versions still achieve top-tier performance among open-source models. The model checkpoints are available at h t t p s : / / g i t h u b . c o m / d e e p s e e k - a i / D e e p Work 21 A Contributions and Acknowledgments 27 B DeepSeek-V2-Lite: A 16B Model Equipped with MLA and DeepSeekMoE 29 2 B.1 Model Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

or generating a report. Applications that integrate LLMs but don’t use them to control workflow execution—think simple chatbots, single-turn LLMs, or sentiment classifiers—are not agents. More concretely manage workflow execution and make decisions. It recognizes when a workflow is complete and can proactively correct its actions if needed. In case 
 of failure, it can halt execution and transfer control design foundations In its most fundamental form, an agent consists of three core components: 01 Model The LLM powering the agent’s reasoning and decision-making 02 Tools External functions or APIs the

Section. Export The following section deals the various model components, required to export to the .nif format. Base Model Create your base model and configure the settings on the object, refer to the objects and update their collision settings, refer to the Collision Section. Armatures Create a rigged model and configure the flags for each selected bone, refer to the Armature Section. Animations Not yet Import/Export execution via the Information View. There are 3 levels of logging information - Information : This is general progress information - Warning : There was an issue that did not cause the execution to

1.2.2 Export The following section deals the various model components, required to export to the .nif format. Base Model Create your base model and configure the settings on the object, refer to the objects and update their collision settings, refer to the Collision Section. Armatures Create a rigged model and configure the flags for each selected bone, refer to the Armature Section. Animations Not yet Import/Export execution via the Information View. There are 3 levels of logging information - Information: This is general progress information - Warning: There was an issue that did not cause the execution to fail

1.2.2 Export The following section deals the various model components, required to export to the .nif format. Base Model Create your base model and configure the settings on the object, refer to the objects and update their collision settings, refer to the Collision Section. Armatures Create a rigged model and configure the flags for each selected bone, refer to the Armature Section. Animations Not yet Import/Export execution via the Information View. There are 3 levels of logging information - Information : This is general progress information - Warning : There was an issue that did not cause the execution to

Section. Export The following section deals the various model components, required to export to the .nif format. Base Model Create your base model and configure the settings on the object, refer to the objects and update their collision settings, refer to the Collision Section. Armatures Create a rigged model and configure the flags for each selected bone, refer to the Armature Section. Animations Not yet Import/Export execution via the Information View. There are 3 levels of logging information - Information: This is general progress information - Warning: There was an issue that did not cause the execution to fail

source/requirements.txt At that point, if the console does not show any trace of pyside_postinstall.py script execution, type in: $ python ./venv/bin/pyside_postinstall.py -install Note: MacOS: running these lines user=’user A’ eye="left"/> model="oculus_dk2"> 1.0, 1.0, -1.0 -1 user=’user A’ eye="left"/> model="oculus_dk2"> 1.0, 1.0, -1.0 -1

source/requirements.txt At that point, if the console does not show any trace of pyside_postinstall.py script execution, type in: $ python ./venv/bin/pyside_postinstall.py -install Note MacOS: running these lines eye="left"/> model="oculus_dk2"> 1.0, 1.0, -1.0 eye="left"/> model="oculus_dk2"> 1.0, 1.0, -1.0

Though by default computers use RGB, they can also convert to CMYK (the subtractive model), or a perceptual model like LAB. In all cases this is just a different way of indicating how the colors relate different color model (CMYK) and it has often access to a lower range of colors (called a gamut). A naive person would suggest the following solution: do your work within the CMYK color model! But there are this particular cube uses red, green, and blue as its axes, we say that our cube is in the RGB color model. There are many more color models. For example, if we were to balance our cube on the black corner