"tesla=550.127.08" }, "networking": { "disable_internet_endpoint": false }, "containers": [ { "image": "registry-vpc.cn-shanghai.aliyuncs.com/xxx/yyy:zzz", "prepare": { "pythonRequirements": [ "numpy==1.16.4", "absl-py==0.11.0" ] }, "command": "python app.py", "port":...
pip install numpy pip install tritonclient[http] pip install pillow pip install gevent Access to NCv3-series VMs for your Azure subscription. Important You might need to request a quota increase for your subscription before you can use this series of VMs. For more information, see NCv3-serie...
importnumpyasnpimportpandasaspdimportrequestsdefcreate_tf_serving_json(data):return{'inputs': {name: data[name].tolist()fornameindata.keys()}ifisinstance(data, dict)elsedata.tolist()}defscore_model(model_uri, databricks_token, data):headers = {"Authorization":f"Bearer{databricks_token}","Co...
numpy 2 support; update docs Feb 19, 2025 requirements.txt Update requirements.txt Feb 19, 2025 setup.py rewrite all remaining pyx for callvar to py Oct 23, 2024 README Code of conduct BSD-3-Clause license Latest Release: Github:
fromkeras.applications.vgg16importVGG16fromkeras.applications.vgg16importpreprocess_inputimportkeras.backendasKimportnumpyasnpimportjsonimportshap# load pre-trained model and choose two images to explainmodel=VGG16(weights='imagenet',include_top=True)X,y=shap.datasets.imagenet50()to_explain=X[[39,41...
Consequently, there are many opportunities to speed up the training of your model by utilizing all the cores on your computer. This is especially true if your model has a high degree of parallelism, like a random decision forest. A random decision forest is an easy type of model to parallel...
# Sample script to run LLM with the static key-value cache and PyTorch compilationfromtransformersimportAutoModelForCausalLM,AutoTokenizer,StaticCacheimporttorchfromtypingimportOptionalimportosdevice=torch.device("cuda:0"iftorch.cuda.is_available()else"cpu")os.environ["TOKENIZERS_PARALLELISM"]="false"...
Megatron-LM: Training multi-billion parameter language models using model parallelism. arXiv preprint arXiv:1909.08053, 2019. Sidorov et al. (2020) Oleksii Sidorov, Ronghang Hu, Marcus Rohrbach, and Amanpreet Singh. TextCaps: a dataset for image captioning with reading comprehension. In Euro...
Adjustments: Depending on your specific hardware and training requirements, you might need to adjust parameters such as the size of the model parallelism, batch sizes, and optimization settings. Refer to the configuration documentation for detailed descriptions of each parameter. 4. Data preparation Tok...
Model parallelism and large model inference The LMI container documentation SageMaker AI endpoint parameters for LMI Deploying uncompressed models Deploy large models for inference with TorchServe Deployment guardrails Auto-Rollback Configuration and Monitoring Blue/Green Deployments Use all at once traffic sh...