hfModelId large_stringlengths 11 68 | smModelId large_stringlengths 15 86 ⌀ | serverlessCustomizationSupport bool 2
classes | serverfulTrainingSupport bool 2
classes | deployAvailability bool 1
class | trainingAvailability bool 2
classes | hasMultipleVariants bool 2
classes | endpointCode large_stringlengths 380 1.25k ⌀ | endpointLinks large_stringclasses 10
values | training_hfCode large_stringclasses 33
values | training_hfLinks large_stringclasses 3
values | deployRedirectionLink large_stringlengths 153 272 ⌀ | customizeRedirectionLink large_stringlengths 206 266 ⌀ | rlaifCode large_stringclasses 1
value | rlaifLabel large_stringclasses 1
value | rlaifLinks large_stringclasses 1
value | rlvrCode large_stringclasses 1
value | rlvrLabel large_stringclasses 1
value | rlvrLinks large_stringclasses 1
value | sftCode large_stringclasses 1
value | sftLabel large_stringclasses 1
value | sftLinks large_stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
aisingapore/SEA-LION-v1-7B | huggingface-llm-sealion-7b | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-sealion-7b")
example_payloads = model.retrieve_... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=aisingapore%2Fsea-lion-v1-7b&smModelId=huggingface-llm-sealion-7b&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
aisingapore/SEA-LION-v1-7B-IT | huggingface-llm-sealion-7b-instruct | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-sealion-7b-instruct")
example_payloads = model.... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=aisingapore%2Fsea-lion-v1-7b-it&smModelId=huggingface-llm-sealion-7b-instruct&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
allenai/Olmo-3-7B-Instruct | huggingface-textgeneration-olmo-3-7b-instruct | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-textgeneration-olmo-3-7b-instruct")
example_payload... | [{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=allenai%2Folmo-3-7b-instruct&smModelId=huggingface-textgeneration-olmo-3-7b-instruct&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
amazon/FalconLite | huggingface-llm-amazon-falconlite | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-amazon-falconlite")
example_payloads = model.re... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=amazon%2Ffalconlite&smModelId=huggingface-llm-amazon-falconlite&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
amazon/FalconLite2 | huggingface-llm-amazon-falconlite2 | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-amazon-falconlite2")
example_payloads = model.r... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=amazon%2Ffalconlite2&smModelId=huggingface-llm-amazon-falconlite2&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
amazon/MistralLite | huggingface-llm-amazon-mistrallite | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-amazon-mistrallite")
example_payloads = model.r... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=amazon%2Fmistrallite&smModelId=huggingface-llm-amazon-mistrallite&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
amazon/chronos-2 | pytorch-forecasting-chronos-2 | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="pytorch-forecasting-chronos-2")
example_payloads = model.retrieve_all_example... | [{"label": "Using Chronos-2 on SageMaker JumpStart", "href": "https://github.com/amazon-science/chronos-forecasting/blob/main/notebooks/deploy-chronos-to-amazon-sagemaker.ipynb"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=amazon%2Fchronos-2&smModelId=pytorch-forecasting-chronos-2&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
aws-neuron/Llama-2-7b-chat-hf-seqlen-2048-bs-4 | meta-textgenerationneuron-llama-2-7b-f | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "meta-textgenerationneuron-llama-2-7b-f"
model = JumpStartModel(model_id=model_id, i... | [] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=aws-neuron%2Fllama-2-7b-chat-hf-seqlen-2048-bs-4&smModelId=meta-textgenerationneuron-llama-2-7b-f&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
baichuan-inc/Baichuan2-7B-Base | huggingface-llm-baichuan2-7b-base-fp16 | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-baichuan2-7b-base-fp16")
example_payloads = mod... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=baichuan-inc%2Fbaichuan2-7b-base&smModelId=huggingface-llm-baichuan2-7b-base-fp16&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
berkeley-nest/Starling-LM-7B-alpha | huggingface-llm-berkeley-nest-starling-lm-7b-alpha | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-berkeley-nest-starling-lm-7b-alpha")
example_pa... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=berkeley-nest%2Fstarling-lm-7b-alpha&smModelId=huggingface-llm-berkeley-nest-starling-lm-7b-alpha&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
bigcode/starcoder | huggingface-llm-starcoder | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-starcoder")
example_payloads = model.retrieve_a... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=bigcode%2Fstarcoder&smModelId=huggingface-llm-starcoder&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
bigcode/starcoderbase | huggingface-llm-starcoderbase | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-starcoderbase")
example_payloads = model.retrie... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=bigcode%2Fstarcoderbase&smModelId=huggingface-llm-starcoderbase&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
bigscience/bloom-7b1 | huggingface-textgeneration1-bloom-7b1 | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-textgeneration1-bloom-7b1")
example_payloads = mode... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=bigscience%2Fbloom-7b1&smModelId=huggingface-textgeneration1-bloom-7b1&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=bigscience%2Fbloom-7b1&smModelId=huggingface-textgeneration1-bloom-7b1&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
bigscience/bloomz-7b1 | huggingface-textgeneration1-bloomz-7b1-fp16 | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-textgeneration1-bloomz-7b1-fp16")
example_payloads ... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | # Fine-tune a Hugging Face Hub model using the SageMaker Python SDK v3.
# See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch
import boto3
from sagemaker.train.model_trainer import ModelTrainer
from sagemaker.core.training.configs import Compute, SourceCode
from sagemaker.core import image_ur... | [{"href": "https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart-foundation-models/domain-adaption-finetuning-gpt-j-6b.ipynb", "label": "Large Language Model (LLM): Run Domain Adaptation fine-tuning in Amazon SageMaker JumpStart"}, {"href": "https://aws.amazon.com/sagema... | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=bigscience%2Fbloomz-7b1&smModelId=huggingface-textgeneration1-bloomz-7b1-fp16&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=bigscience%2Fbloomz-7b1&smModelId=huggingface-textgeneration1-bloomz-7b1-fp16&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
black-forest-labs/FLUX.1-schnell | huggingface-txt2img-black-forest-labs-flux-1-schnell | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-txt2img-black-forest-labs-flux-1-schnell")
example_... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=black-forest-labs%2Fflux.1-schnell&smModelId=huggingface-txt2img-black-forest-labs-flux-1-schnell&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
black-forest-labs/FLUX.2-klein-base-4B | null | false | null | true | false | null | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-img2img-flux-2-klein-base-4b")
example_payloads = m... | [{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}] | null | null | null | null | null | null | null | null | null | null | null | null | null |
codellama/CodeLlama-13b-Instruct-hf | meta-textgeneration-llama-codellama-13b-instruct | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="meta-textgeneration-llama-codellama-13b-instruct")
example_payl... | [{"label": "Large Language Model (LLM): Run Inference in Amazon SageMaker JumpStart", "href": "https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart-foundation-models/text-generation-chatbot.ipynb"}, {"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com... | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=codellama%2Fcodellama-13b-instruct-hf&smModelId=meta-textgeneration-llama-codellama-13b-instruct&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
codellama/CodeLlama-13b-Python-hf | null | false | null | true | false | null | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="meta-textgeneration-llama-codellama-13b-python")
example_payloa... | [{"href": "https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart-foundation-models/text-generation-chatbot.ipynb", "label": "Large Language Model (LLM): Run Inference in Amazon SageMaker JumpStart"}, {"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon... | null | null | null | null | null | null | null | null | null | null | null | null | null |
codellama/CodeLlama-13b-hf | meta-textgeneration-llama-codellama-13b | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="meta-textgeneration-llama-codellama-13b")
example_payloads = mo... | [{"label": "Large Language Model (LLM): Run Inference in Amazon SageMaker JumpStart", "href": "https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart-foundation-models/text-generation-chatbot.ipynb"}, {"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com... | # Fine-tune a gated Hugging Face Hub model using the SageMaker Python SDK v3.
# This model requires a Hugging Face token to download weights.
# See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch
import boto3
from sagemaker.train.model_trainer import ModelTrainer
from sagemaker.core.training.... | [] | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=codellama%2Fcodellama-13b-hf&smModelId=meta-textgeneration-llama-codellama-13b&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=codellama%2Fcodellama-13b-hf&smModelId=meta-textgeneration-llama-codellama-13b&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
codellama/CodeLlama-34b-Instruct-hf | meta-textgeneration-llama-codellama-34b-instruct | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="meta-textgeneration-llama-codellama-34b-instruct")
example_payl... | [{"label": "Large Language Model (LLM): Run Inference in Amazon SageMaker JumpStart", "href": "https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart-foundation-models/text-generation-chatbot.ipynb"}, {"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com... | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=codellama%2Fcodellama-34b-instruct-hf&smModelId=meta-textgeneration-llama-codellama-34b-instruct&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
codellama/CodeLlama-34b-Python-hf | meta-textgeneration-llama-codellama-34b-python | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="meta-textgeneration-llama-codellama-34b-python")
example_payloa... | [{"label": "Large Language Model (LLM): Run Inference in Amazon SageMaker JumpStart", "href": "https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart-foundation-models/text-generation-chatbot.ipynb"}, {"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com... | # Fine-tune a gated Hugging Face Hub model using the SageMaker Python SDK v3.
# This model requires a Hugging Face token to download weights.
# See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch
import boto3
from sagemaker.train.model_trainer import ModelTrainer
from sagemaker.core.training.... | [] | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=codellama%2Fcodellama-34b-python-hf&smModelId=meta-textgeneration-llama-codellama-34b-python&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=codellama%2Fcodellama-34b-python-hf&smModelId=meta-textgeneration-llama-codellama-34b-python&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
codellama/CodeLlama-34b-hf | meta-textgeneration-llama-codellama-34b | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="meta-textgeneration-llama-codellama-34b")
example_payloads = mo... | [{"label": "Large Language Model (LLM): Run Inference in Amazon SageMaker JumpStart", "href": "https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart-foundation-models/text-generation-chatbot.ipynb"}, {"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com... | # Fine-tune a gated Hugging Face Hub model using the SageMaker Python SDK v3.
# This model requires a Hugging Face token to download weights.
# See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch
import boto3
from sagemaker.train.model_trainer import ModelTrainer
from sagemaker.core.training.... | [] | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=codellama%2Fcodellama-34b-hf&smModelId=meta-textgeneration-llama-codellama-34b&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=codellama%2Fcodellama-34b-hf&smModelId=meta-textgeneration-llama-codellama-34b&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
codellama/CodeLlama-70b-Instruct-hf | meta-textgeneration-llama-codellama-70b-instruct | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="meta-textgeneration-llama-codellama-70b-instruct")
example_payl... | [{"label": "Large Language Model (LLM): Run Inference in Amazon SageMaker JumpStart", "href": "https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart-foundation-models/text-generation-chatbot.ipynb"}, {"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com... | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=codellama%2Fcodellama-70b-instruct-hf&smModelId=meta-textgeneration-llama-codellama-70b-instruct&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
codellama/CodeLlama-70b-Python-hf | meta-textgeneration-llama-codellama-70b-python | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="meta-textgeneration-llama-codellama-70b-python")
example_payloa... | [{"label": "Large Language Model (LLM): Run Inference in Amazon SageMaker JumpStart", "href": "https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart-foundation-models/text-generation-chatbot.ipynb"}, {"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com... | # Fine-tune a gated Hugging Face Hub model using the SageMaker Python SDK v3.
# This model requires a Hugging Face token to download weights.
# See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch
import boto3
from sagemaker.train.model_trainer import ModelTrainer
from sagemaker.core.training.... | [] | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=codellama%2Fcodellama-70b-python-hf&smModelId=meta-textgeneration-llama-codellama-70b-python&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=codellama%2Fcodellama-70b-python-hf&smModelId=meta-textgeneration-llama-codellama-70b-python&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
codellama/CodeLlama-70b-hf | meta-textgenerationneuron-llama-codellama-70b | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="meta-textgeneration-llama-codellama-70b")
example_payloads = mo... | [{"label": "Large Language Model (LLM): Run Inference in Amazon SageMaker JumpStart", "href": "https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart-foundation-models/text-generation-chatbot.ipynb"}, {"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com... | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=codellama%2Fcodellama-70b-hf&smModelId=meta-textgenerationneuron-llama-codellama-70b&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
codellama/CodeLlama-7b-Instruct-hf | meta-textgeneration-llama-codellama-7b-instruct | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="meta-textgeneration-llama-codellama-7b-instruct")
example_paylo... | [{"label": "Large Language Model (LLM): Run Inference in Amazon SageMaker JumpStart", "href": "https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart-foundation-models/text-generation-chatbot.ipynb"}, {"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com... | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=codellama%2Fcodellama-7b-instruct-hf&smModelId=meta-textgeneration-llama-codellama-7b-instruct&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
codellama/CodeLlama-7b-Python-hf | meta-textgenerationneuron-llama-codellama-7b-python | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="meta-textgeneration-llama-codellama-7b-python")
example_payload... | [{"label": "Large Language Model (LLM): Run Inference in Amazon SageMaker JumpStart", "href": "https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart-foundation-models/text-generation-chatbot.ipynb"}, {"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com... | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=codellama%2Fcodellama-7b-python-hf&smModelId=meta-textgenerationneuron-llama-codellama-7b-python&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
codellama/CodeLlama-7b-hf | meta-textgenerationneuron-llama-codellama-7b | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="meta-textgeneration-llama-codellama-7b")
example_payloads = mod... | [{"label": "Large Language Model (LLM): Run Inference in Amazon SageMaker JumpStart", "href": "https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart-foundation-models/text-generation-chatbot.ipynb"}, {"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com... | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=codellama%2Fcodellama-7b-hf&smModelId=meta-textgenerationneuron-llama-codellama-7b&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
cross-encoder/nli-MiniLM2-L6-H768 | huggingface-zstc-cross-encoder-nli-minilm2-l6-h768 | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-zstc-cross-encoder-nli-minilm2-l6-h768"
endpoint_input = {'sequences': '... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=cross-encoder%2Fnli-minilm2-l6-h768&smModelId=huggingface-zstc-cross-encoder-nli-minilm2-l6-h768&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
cross-encoder/nli-deberta-base | huggingface-zstc-cross-encoder-nli-deberta-base | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-zstc-cross-encoder-nli-deberta-base"
endpoint_input = {'sequences': 'one... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=cross-encoder%2Fnli-deberta-base&smModelId=huggingface-zstc-cross-encoder-nli-deberta-base&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
cross-encoder/nli-distilroberta-base | huggingface-zstc-cross-encoder-nli-distilroberta-base | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-zstc-cross-encoder-nli-distilroberta-base"
endpoint_input = {'sequences'... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=cross-encoder%2Fnli-distilroberta-base&smModelId=huggingface-zstc-cross-encoder-nli-distilroberta-base&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
cross-encoder/nli-roberta-base | huggingface-zstc-cross-encoder-nli-roberta-base | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-zstc-cross-encoder-nli-roberta-base"
endpoint_input = {'sequences': 'one... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=cross-encoder%2Fnli-roberta-base&smModelId=huggingface-zstc-cross-encoder-nli-roberta-base&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
cyberagent/calm2-7b-chat | huggingface-llm-calm2-7b-chat-bf16 | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-calm2-7b-chat-bf16")
example_payloads = model.r... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | # Fine-tune a Hugging Face Hub model using the SageMaker Python SDK v3.
# See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch
import boto3
from sagemaker.train.model_trainer import ModelTrainer
from sagemaker.core.training.configs import Compute, SourceCode
from sagemaker.core import image_ur... | [] | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=cyberagent%2Fcalm2-7b-chat&smModelId=huggingface-llm-calm2-7b-chat-bf16&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=cyberagent%2Fcalm2-7b-chat&smModelId=huggingface-llm-calm2-7b-chat-bf16&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
deepseek-ai/DeepSeek-OCR | deepseek-vlm-deepseek-ocr | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="deepseek-vlm-deepseek-ocr")
example_payloads = model.retrieve_a... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=deepseek-ai%2Fdeepseek-ocr&smModelId=deepseek-vlm-deepseek-ocr&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
deepseek-ai/DeepSeek-R1 | deepseek-llm-r1 | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="deepseek-llm-r1")
example_payloads = model.retrieve_all_example... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=deepseek-ai%2Fdeepseek-r1&smModelId=deepseek-llm-r1&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
deepseek-ai/DeepSeek-R1-0528 | deepseek-llm-r1-0528 | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="deepseek-llm-r1-0528")
example_payloads = model.retrieve_all_ex... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=deepseek-ai%2Fdeepseek-r1-0528&smModelId=deepseek-llm-r1-0528&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
deepseek-ai/DeepSeek-R1-Distill-Llama-70B | deepseek-llm-r1-distill-llama-70b | true | false | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="deepseek-llm-r1-distill-llama-70b")
example_payloads = model.re... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=deepseek-ai%2Fdeepseek-r1-distill-llama-70b&smModelId=deepseek-llm-r1-distill-llama-70b&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=deepseek-ai%2Fdeepseek-r1-distill-llama-70b&smModelId=deepseek-llm-r1-distill-llama-70b&supportServerless=true&supportServerful=false&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
deepseek-ai/DeepSeek-R1-Distill-Llama-8B | deepseek-llm-r1-distill-llama-8b | true | false | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="deepseek-llm-r1-distill-llama-8b")
example_payloads = model.ret... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=deepseek-ai%2Fdeepseek-r1-distill-llama-8b&smModelId=deepseek-llm-r1-distill-llama-8b&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=deepseek-ai%2Fdeepseek-r1-distill-llama-8b&smModelId=deepseek-llm-r1-distill-llama-8b&supportServerless=true&supportServerful=false&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B | deepseek-llm-r1-distill-qwen-1-5b | true | false | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="deepseek-llm-r1-distill-qwen-1-5b")
example_payloads = model.re... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=deepseek-ai%2Fdeepseek-r1-distill-qwen-1.5b&smModelId=deepseek-llm-r1-distill-qwen-1-5b&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=deepseek-ai%2Fdeepseek-r1-distill-qwen-1.5b&smModelId=deepseek-llm-r1-distill-qwen-1-5b&supportServerless=true&supportServerful=false&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
deepseek-ai/DeepSeek-R1-Distill-Qwen-14B | deepseek-llm-r1-distill-qwen-14b | true | false | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="deepseek-llm-r1-distill-qwen-14b")
example_payloads = model.ret... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=deepseek-ai%2Fdeepseek-r1-distill-qwen-14b&smModelId=deepseek-llm-r1-distill-qwen-14b&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=deepseek-ai%2Fdeepseek-r1-distill-qwen-14b&smModelId=deepseek-llm-r1-distill-qwen-14b&supportServerless=true&supportServerful=false&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
deepseek-ai/DeepSeek-R1-Distill-Qwen-32B | deepseek-llm-r1-distill-qwen-32b | true | false | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="deepseek-llm-r1-distill-qwen-32b")
example_payloads = model.ret... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=deepseek-ai%2Fdeepseek-r1-distill-qwen-32b&smModelId=deepseek-llm-r1-distill-qwen-32b&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=deepseek-ai%2Fdeepseek-r1-distill-qwen-32b&smModelId=deepseek-llm-r1-distill-qwen-32b&supportServerless=true&supportServerful=false&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
deepseek-ai/DeepSeek-R1-Distill-Qwen-7B | deepseek-llm-r1-distill-qwen-7b | true | false | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="deepseek-llm-r1-distill-qwen-7b")
example_payloads = model.retr... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=deepseek-ai%2Fdeepseek-r1-distill-qwen-7b&smModelId=deepseek-llm-r1-distill-qwen-7b&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=deepseek-ai%2Fdeepseek-r1-distill-qwen-7b&smModelId=deepseek-llm-r1-distill-qwen-7b&supportServerless=true&supportServerful=false&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
deepseek-ai/DeepSeek-V3.1 | deepseek-llm-deepseek-v3-1 | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="deepseek-llm-deepseek-v3-1")
example_payloads = model.retrieve_... | [{"label": "SageMaker JumpStart Examples", "href": "https://github.com/aws/amazon-sagemaker-examples/tree/main/sagemaker-jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=deepseek-ai%2Fdeepseek-v3.1&smModelId=deepseek-llm-deepseek-v3-1&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
deepseek-ai/DeepSeek-V3.2 | deepseek-llm-deepseek-v3-2 | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="deepseek-llm-deepseek-v3-2")
example_payloads = model.retrieve_... | [{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=deepseek-ai%2Fdeepseek-v3.2&smModelId=deepseek-llm-deepseek-v3-2&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
distilbert/distilbert-base-cased | huggingface-eqa-distilbert-base-cased | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-eqa-distilbert-base-cased")
example_payloads = mode... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | # Fine-tune a Hugging Face Hub model using the SageMaker Python SDK v3.
# See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch
import boto3
from sagemaker.train.model_trainer import ModelTrainer
from sagemaker.core.training.configs import Compute, SourceCode
from sagemaker.core import image_ur... | [] | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=distilbert%2Fdistilbert-base-cased&smModelId=huggingface-eqa-distilbert-base-cased&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=distilbert%2Fdistilbert-base-cased&smModelId=huggingface-eqa-distilbert-base-cased&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
distilbert/distilbert-base-multilingual-cased | huggingface-eqa-distilbert-base-multilingual-cased | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-eqa-distilbert-base-multilingual-cased")
example_pa... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | # Fine-tune a Hugging Face Hub model using the SageMaker Python SDK v3.
# See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch
import boto3
from sagemaker.train.model_trainer import ModelTrainer
from sagemaker.core.training.configs import Compute, SourceCode
from sagemaker.core import image_ur... | [] | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=distilbert%2Fdistilbert-base-multilingual-cased&smModelId=huggingface-eqa-distilbert-base-multilingual-cased&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=distilbert%2Fdistilbert-base-multilingual-cased&smModelId=huggingface-eqa-distilbert-base-multilingual-cased&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
distilbert/distilbert-base-uncased | huggingface-eqa-distilbert-base-uncased | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-eqa-distilbert-base-uncased")
example_payloads = mo... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | # Fine-tune a Hugging Face Hub model using the SageMaker Python SDK v3.
# See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch
import boto3
from sagemaker.train.model_trainer import ModelTrainer
from sagemaker.core.training.configs import Compute, SourceCode
from sagemaker.core import image_ur... | [] | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=distilbert%2Fdistilbert-base-uncased&smModelId=huggingface-eqa-distilbert-base-uncased&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=distilbert%2Fdistilbert-base-uncased&smModelId=huggingface-eqa-distilbert-base-uncased&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
distilbert/distilroberta-base | huggingface-eqa-distilroberta-base | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-eqa-distilroberta-base")
example_payloads = model.r... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | # Fine-tune a Hugging Face Hub model using the SageMaker Python SDK v3.
# See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch
import boto3
from sagemaker.train.model_trainer import ModelTrainer
from sagemaker.core.training.configs import Compute, SourceCode
from sagemaker.core import image_ur... | [] | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=distilbert%2Fdistilroberta-base&smModelId=huggingface-eqa-distilroberta-base&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=distilbert%2Fdistilroberta-base&smModelId=huggingface-eqa-distilroberta-base&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
dphn/dolphin-2.2.1-mistral-7b | huggingface-llm-dolphin-2-2-1-mistral-7b | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-dolphin-2-2-1-mistral-7b")
example_payloads = m... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=dphn%2Fdolphin-2.2.1-mistral-7b&smModelId=huggingface-llm-dolphin-2-2-1-mistral-7b&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
dphn/dolphin-2.5-mixtral-8x7b | huggingface-llm-dolphin-2-5-mixtral-8x7b | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-dolphin-2-5-mixtral-8x7b")
example_payloads = m... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=dphn%2Fdolphin-2.5-mixtral-8x7b&smModelId=huggingface-llm-dolphin-2-5-mixtral-8x7b&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
dphn/dolphin-2.7-mixtral-8x7b | huggingface-llm-dolphin-2-7-mixtral-8x7b | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-dolphin-2-7-mixtral-8x7b")
example_payloads = m... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=dphn%2Fdolphin-2.7-mixtral-8x7b&smModelId=huggingface-llm-dolphin-2-7-mixtral-8x7b&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
dphn/dolphin-2.9-llama3-8b | huggingface-llm-cognitive-dolphin-29-llama3-8b | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-cognitive-dolphin-29-llama3-8b")
example_payloa... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=dphn%2Fdolphin-2.9-llama3-8b&smModelId=huggingface-llm-cognitive-dolphin-29-llama3-8b&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
elastic/distilbert-base-cased-finetuned-conll03-english | null | false | null | true | false | null | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-ner-distilbert-base-cased-finetuned-conll03-eng"
endpoint_input = "My na... | [{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}] | null | null | null | null | null | null | null | null | null | null | null | null | null |
elastic/distilbert-base-uncased-finetuned-conll03-english | null | false | null | true | false | null | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-ner-distilbert-base-uncased-finetuned-conll03-eng"
endpoint_input = "My ... | [{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}] | null | null | null | null | null | null | null | null | null | null | null | null | null |
elyza/ELYZA-japanese-Llama-2-13b-instruct | huggingface-llm-elyza-japanese-llama-2-13b-chat | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-elyza-japanese-llama-2-13b-chat")
example_paylo... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | # Fine-tune a gated Hugging Face Hub model using the SageMaker Python SDK v3.
# This model requires a Hugging Face token to download weights.
# See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch
import boto3
from sagemaker.train.model_trainer import ModelTrainer
from sagemaker.core.training.... | [] | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=elyza%2Felyza-japanese-llama-2-13b-instruct&smModelId=huggingface-llm-elyza-japanese-llama-2-13b-chat&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=elyza%2Felyza-japanese-llama-2-13b-instruct&smModelId=huggingface-llm-elyza-japanese-llama-2-13b-chat&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
elyza/ELYZA-japanese-Llama-2-7b-instruct | huggingface-llm-elyza-japanese-llama-2-7b-chat-bf16 | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-elyza-japanese-llama-2-7b-chat-bf16")
example_p... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | # Fine-tune a gated Hugging Face Hub model using the SageMaker Python SDK v3.
# This model requires a Hugging Face token to download weights.
# See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch
import boto3
from sagemaker.train.model_trainer import ModelTrainer
from sagemaker.core.training.... | [] | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=elyza%2Felyza-japanese-llama-2-7b-instruct&smModelId=huggingface-llm-elyza-japanese-llama-2-7b-chat-bf16&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=elyza%2Felyza-japanese-llama-2-7b-instruct&smModelId=huggingface-llm-elyza-japanese-llama-2-7b-chat-bf16&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
emrecan/bert-base-turkish-cased-allnli_tr | huggingface-zstc-emrecan-bert-base-turkish-cased-allnli-tr | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-zstc-emrecan-bert-base-turkish-cased-allnli-tr"
endpoint_input = {'seque... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=emrecan%2Fbert-base-turkish-cased-allnli_tr&smModelId=huggingface-zstc-emrecan-bert-base-turkish-cased-allnli-tr&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
facebook/bart-large-mnli | huggingface-zstc-facebook-bart-large-mnli | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-zstc-facebook-bart-large-mnli"
endpoint_input = {'sequences': 'one day I... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=facebook%2Fbart-large-mnli&smModelId=huggingface-zstc-facebook-bart-large-mnli&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
google-bert/bert-base-cased | huggingface-eqa-bert-base-cased | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-eqa-bert-base-cased")
example_payloads = model.retr... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | # Fine-tune a Hugging Face Hub model using the SageMaker Python SDK v3.
# See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch
import boto3
from sagemaker.train.model_trainer import ModelTrainer
from sagemaker.core.training.configs import Compute, SourceCode
from sagemaker.core import image_ur... | [] | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google-bert%2Fbert-base-cased&smModelId=huggingface-eqa-bert-base-cased&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google-bert%2Fbert-base-cased&smModelId=huggingface-eqa-bert-base-cased&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
google-bert/bert-base-multilingual-cased | huggingface-eqa-bert-base-multilingual-cased | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-eqa-bert-base-multilingual-cased")
example_payloads... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | # Fine-tune a Hugging Face Hub model using the SageMaker Python SDK v3.
# See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch
import boto3
from sagemaker.train.model_trainer import ModelTrainer
from sagemaker.core.training.configs import Compute, SourceCode
from sagemaker.core import image_ur... | [] | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google-bert%2Fbert-base-multilingual-cased&smModelId=huggingface-eqa-bert-base-multilingual-cased&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google-bert%2Fbert-base-multilingual-cased&smModelId=huggingface-eqa-bert-base-multilingual-cased&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
google-bert/bert-base-multilingual-uncased | huggingface-eqa-bert-base-multilingual-uncased | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-eqa-bert-base-multilingual-uncased")
example_payloa... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google-bert%2Fbert-base-multilingual-uncased&smModelId=huggingface-eqa-bert-base-multilingual-uncased&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google-bert%2Fbert-base-multilingual-uncased&smModelId=huggingface-eqa-bert-base-multilingual-uncased&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
google-bert/bert-base-uncased | huggingface-eqa-bert-base-uncased | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-eqa-bert-base-uncased")
example_payloads = model.re... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google-bert%2Fbert-base-uncased&smModelId=huggingface-eqa-bert-base-uncased&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google-bert%2Fbert-base-uncased&smModelId=huggingface-eqa-bert-base-uncased&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
google-bert/bert-large-cased | huggingface-eqa-bert-large-cased | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-eqa-bert-large-cased")
example_payloads = model.ret... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | # Fine-tune a Hugging Face Hub model using the SageMaker Python SDK v3.
# See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch
import boto3
from sagemaker.train.model_trainer import ModelTrainer
from sagemaker.core.training.configs import Compute, SourceCode
from sagemaker.core import image_ur... | [] | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google-bert%2Fbert-large-cased&smModelId=huggingface-eqa-bert-large-cased&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google-bert%2Fbert-large-cased&smModelId=huggingface-eqa-bert-large-cased&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
google-bert/bert-large-cased-whole-word-masking | huggingface-eqa-bert-large-cased-whole-word-masking | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-eqa-bert-large-cased-whole-word-masking")
example_p... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google-bert%2Fbert-large-cased-whole-word-masking&smModelId=huggingface-eqa-bert-large-cased-whole-word-masking&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google-bert%2Fbert-large-cased-whole-word-masking&smModelId=huggingface-eqa-bert-large-cased-whole-word-masking&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
google/bigbird-pegasus-large-arxiv | huggingface-summarization-bigbird-pegasus-large-arxiv | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-summarization-bigbird-pegasus-large-arxiv"
endpoint_input = "The tower i... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fbigbird-pegasus-large-arxiv&smModelId=huggingface-summarization-bigbird-pegasus-large-arxiv&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
google/bigbird-pegasus-large-pubmed | huggingface-summarization-bigbird-pegasus-large-pubmed | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-summarization-bigbird-pegasus-large-pubmed"
endpoint_input = "The tower ... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fbigbird-pegasus-large-pubmed&smModelId=huggingface-summarization-bigbird-pegasus-large-pubmed&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
google/flan-t5-base | huggingface-text2text-flan-t5-base | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-text2text-flan-t5-base")
example_payloads = model.r... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | # Fine-tune a Hugging Face Hub model using the SageMaker Python SDK v3.
# See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch
import boto3
from sagemaker.train.model_trainer import ModelTrainer
from sagemaker.core.training.configs import Compute, SourceCode
from sagemaker.core import image_ur... | [{"href": "https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart-foundation-models/instruction-fine-tuning-flan-t5.ipynb", "label": "Large Language Model (LLM): Run Instruction-tuning in Amazon SageMaker JumpStart"}, {"href": "https://aws.amazon.com/sagemaker/jumpstart",... | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fflan-t5-base&smModelId=huggingface-text2text-flan-t5-base&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fflan-t5-base&smModelId=huggingface-text2text-flan-t5-base&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
google/flan-t5-large | huggingface-text2text-flan-t5-large | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-text2text-flan-t5-large")
example_payloads = model.... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | # Fine-tune a Hugging Face Hub model using the SageMaker Python SDK v3.
# See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch
import boto3
from sagemaker.train.model_trainer import ModelTrainer
from sagemaker.core.training.configs import Compute, SourceCode
from sagemaker.core import image_ur... | [{"href": "https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart-foundation-models/instruction-fine-tuning-flan-t5.ipynb", "label": "Large Language Model (LLM): Run Instruction-tuning in Amazon SageMaker JumpStart"}, {"href": "https://aws.amazon.com/sagemaker/jumpstart",... | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fflan-t5-large&smModelId=huggingface-text2text-flan-t5-large&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fflan-t5-large&smModelId=huggingface-text2text-flan-t5-large&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
google/flan-t5-small | huggingface-text2text-flan-t5-small | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-text2text-flan-t5-small")
example_payloads = model.... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | # Fine-tune a Hugging Face Hub model using the SageMaker Python SDK v3.
# See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch
import boto3
from sagemaker.train.model_trainer import ModelTrainer
from sagemaker.core.training.configs import Compute, SourceCode
from sagemaker.core import image_ur... | [{"href": "https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart-foundation-models/instruction-fine-tuning-flan-t5.ipynb", "label": "Large Language Model (LLM): Run Instruction-tuning in Amazon SageMaker JumpStart"}, {"href": "https://aws.amazon.com/sagemaker/jumpstart",... | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fflan-t5-small&smModelId=huggingface-text2text-flan-t5-small&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fflan-t5-small&smModelId=huggingface-text2text-flan-t5-small&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
google/flan-t5-xl | huggingface-text2text-flan-t5-xl | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-text2text-flan-t5-xl")
example_payloads = model.ret... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | # Fine-tune a Hugging Face Hub model using the SageMaker Python SDK v3.
# See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch
import boto3
from sagemaker.train.model_trainer import ModelTrainer
from sagemaker.core.training.configs import Compute, SourceCode
from sagemaker.core import image_ur... | [{"href": "https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart-foundation-models/instruction-fine-tuning-flan-t5.ipynb", "label": "Large Language Model (LLM): Run Instruction-tuning in Amazon SageMaker JumpStart"}, {"href": "https://aws.amazon.com/sagemaker/jumpstart",... | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fflan-t5-xl&smModelId=huggingface-text2text-flan-t5-xl&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fflan-t5-xl&smModelId=huggingface-text2text-flan-t5-xl&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
google/flan-t5-xxl | huggingface-text2text-flan-t5-xxl | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-text2text-flan-t5-xxl")
example_payloads = model.re... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | # Fine-tune a Hugging Face Hub model using the SageMaker Python SDK v3.
# See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch
import boto3
from sagemaker.train.model_trainer import ModelTrainer
from sagemaker.core.training.configs import Compute, SourceCode
from sagemaker.core import image_ur... | [{"href": "https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart-foundation-models/instruction-fine-tuning-flan-t5.ipynb", "label": "Large Language Model (LLM): Run Instruction-tuning in Amazon SageMaker JumpStart"}, {"href": "https://aws.amazon.com/sagemaker/jumpstart",... | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fflan-t5-xxl&smModelId=huggingface-text2text-flan-t5-xxl&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fflan-t5-xxl&smModelId=huggingface-text2text-flan-t5-xxl&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
google/gemma-2-27b | huggingface-llm-gemma-2-27b | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-gemma-2-27b")
example_payloads = model.retrieve... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fgemma-2-27b&smModelId=huggingface-llm-gemma-2-27b&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
google/gemma-2-27b-it | huggingface-llm-gemma-2-27b-instruct | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-gemma-2-27b-instruct")
example_payloads = model... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fgemma-2-27b-it&smModelId=huggingface-llm-gemma-2-27b-instruct&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
google/gemma-2-2b | huggingface-llm-gemma-2-2b | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-gemma-2-2b")
example_payloads = model.retrieve_... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fgemma-2-2b&smModelId=huggingface-llm-gemma-2-2b&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
google/gemma-2-2b-it | huggingface-llm-gemma-2-2b-instruct | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-gemma-2-2b-instruct")
example_payloads = model.... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fgemma-2-2b-it&smModelId=huggingface-llm-gemma-2-2b-instruct&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
google/gemma-2-9b | huggingface-llm-gemma-2-9b | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-gemma-2-9b")
example_payloads = model.retrieve_... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fgemma-2-9b&smModelId=huggingface-llm-gemma-2-9b&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
google/gemma-2-9b-it | huggingface-llm-gemma-2-9b-instruct | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-gemma-2-9b-instruct")
example_payloads = model.... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fgemma-2-9b-it&smModelId=huggingface-llm-gemma-2-9b-instruct&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
google/gemma-2b | huggingface-llm-gemma-2b | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-gemma-2b")
example_payloads = model.retrieve_al... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | # Fine-tune a gated Hugging Face Hub model using the SageMaker Python SDK v3.
# This model requires a Hugging Face token to download weights.
# See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch
import boto3
from sagemaker.train.model_trainer import ModelTrainer
from sagemaker.core.training.... | [] | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fgemma-2b&smModelId=huggingface-llm-gemma-2b&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fgemma-2b&smModelId=huggingface-llm-gemma-2b&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
google/gemma-2b-it | huggingface-llm-gemma-2b-instruct | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-gemma-2b-instruct")
example_payloads = model.re... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | # Fine-tune a gated Hugging Face Hub model using the SageMaker Python SDK v3.
# This model requires a Hugging Face token to download weights.
# See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch
import boto3
from sagemaker.train.model_trainer import ModelTrainer
from sagemaker.core.training.... | [] | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fgemma-2b-it&smModelId=huggingface-llm-gemma-2b-instruct&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fgemma-2b-it&smModelId=huggingface-llm-gemma-2b-instruct&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
google/gemma-3-1b-it | huggingface-llm-gemma-3-1b-instruct | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-gemma-3-1b-instruct")
example_payloads = model.... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fgemma-3-1b-it&smModelId=huggingface-llm-gemma-3-1b-instruct&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
google/gemma-3-27b-it | huggingface-vlm-gemma-3-27b-instruct | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-vlm-gemma-3-27b-instruct"
model = JumpStartModel(model_id=model_id)
pay... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fgemma-3-27b-it&smModelId=huggingface-vlm-gemma-3-27b-instruct&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
google/gemma-3-4b-it | huggingface-vlm-gemma-3-4b-instruct | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-vlm-gemma-3-4b-instruct"
model = JumpStartModel(model_id=model_id)
payl... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fgemma-3-4b-it&smModelId=huggingface-vlm-gemma-3-4b-instruct&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
google/gemma-4-26B-A4B-it | huggingface-vlm-gemma-4-26b-a4b-it | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-vlm-gemma-4-26b-a4b-it"
model = JumpStartModel(model_id=model_id)
paylo... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fgemma-4-26b-a4b-it&smModelId=huggingface-vlm-gemma-4-26b-a4b-it&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
google/gemma-4-31B-it | huggingface-vlm-gemma-4-31b-it | true | false | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-vlm-gemma-4-31b-it"
model = JumpStartModel(model_id=model_id)
payload =... | [{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fgemma-4-31b-it&smModelId=huggingface-vlm-gemma-4-31b-it&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fgemma-4-31b-it&smModelId=huggingface-vlm-gemma-4-31b-it&supportServerless=true&supportServerful=false&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
google/gemma-4-E2B-it | huggingface-vlm-gemma-4-e2b-instruct | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-vlm-gemma-4-e2b-instruct"
model = JumpStartModel(model_id=model_id)
pay... | [{"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon SageMaker JumpStart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fgemma-4-e2b-it&smModelId=huggingface-vlm-gemma-4-e2b-instruct&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
google/gemma-4-E4B-it | huggingface-vlm-gemma-4-e4b-it | true | false | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-vlm-gemma-4-e4b-it"
model = JumpStartModel(model_id=model_id)
payload =... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fgemma-4-e4b-it&smModelId=huggingface-vlm-gemma-4-e4b-it&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fgemma-4-e4b-it&smModelId=huggingface-vlm-gemma-4-e4b-it&supportServerless=true&supportServerful=false&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
google/gemma-7b | huggingface-llm-gemma-7b | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-gemma-7b")
example_payloads = model.retrieve_al... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | # Fine-tune a gated Hugging Face Hub model using the SageMaker Python SDK v3.
# This model requires a Hugging Face token to download weights.
# See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch
import boto3
from sagemaker.train.model_trainer import ModelTrainer
from sagemaker.core.training.... | [] | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fgemma-7b&smModelId=huggingface-llm-gemma-7b&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fgemma-7b&smModelId=huggingface-llm-gemma-7b&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
google/gemma-7b-it | huggingface-llm-gemma-7b-instruct | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-gemma-7b-instruct")
example_payloads = model.re... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | # Fine-tune a gated Hugging Face Hub model using the SageMaker Python SDK v3.
# This model requires a Hugging Face token to download weights.
# See https://github.com/huggingface/transformers/tree/v4.56.2/examples/pytorch
import boto3
from sagemaker.train.model_trainer import ModelTrainer
from sagemaker.core.training.... | [] | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fgemma-7b-it&smModelId=huggingface-llm-gemma-7b-instruct&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=google%2Fgemma-7b-it&smModelId=huggingface-llm-gemma-7b-instruct&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
gradientai/Llama-3-8B-Instruct-262k | huggingface-llm-gradientai-llama-3-8B-instruct-262k | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-gradientai-llama-3-8B-instruct-262k")
example_p... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=gradientai%2Fllama-3-8b-instruct-262k&smModelId=huggingface-llm-gradientai-llama-3-8B-instruct-262k&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
gradientai/Llama-3-8B-Instruct-Gradient-1048k | huggingface-llm-llama-3-8b-instruct-gradient | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-llm-llama-3-8b-instruct-gradient")
example_payloads... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=gradientai%2Fllama-3-8b-instruct-gradient-1048k&smModelId=huggingface-llm-llama-3-8b-instruct-gradient&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
ibm-research/qcpg-sentences | huggingface-text2text-qcpg-sentences | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="huggingface-text2text-qcpg-sentences")
example_payloads = model... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=ibm-research%2Fqcpg-sentences&smModelId=huggingface-text2text-qcpg-sentences&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
intfloat/e5-base | huggingface-sentencesimilarity-e5-base | false | true | true | true | false | from sagemaker.jumpstart.model import JumpStartModel
import json
model_id = "huggingface-sentencesimilarity-e5-base"
endpoint_input = json.dumps(["How cute your dog is!", "Your dog is so cute."])
model = JumpStartModel(model_id=model_id)
predictor = model.deploy()
response = predictor.predict(endpoint_input)
print(f"... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=intfloat%2Fe5-base&smModelId=huggingface-sentencesimilarity-e5-base&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=intfloat%2Fe5-base&smModelId=huggingface-sentencesimilarity-e5-base&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
intfloat/e5-base-v2 | huggingface-sentencesimilarity-e5-base-v2 | false | true | true | true | false | from sagemaker.jumpstart.model import JumpStartModel
import json
model_id = "huggingface-sentencesimilarity-e5-base-v2"
endpoint_input = json.dumps(["How cute your dog is!", "Your dog is so cute."])
model = JumpStartModel(model_id=model_id)
predictor = model.deploy()
response = predictor.predict(endpoint_input)
print... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=intfloat%2Fe5-base-v2&smModelId=huggingface-sentencesimilarity-e5-base-v2&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=intfloat%2Fe5-base-v2&smModelId=huggingface-sentencesimilarity-e5-base-v2&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
intfloat/e5-large-v2 | huggingface-sentencesimilarity-e5-large-v2 | false | true | true | true | false | from sagemaker.jumpstart.model import JumpStartModel
import json
model_id = "huggingface-sentencesimilarity-e5-large-v2"
endpoint_input = json.dumps(["How cute your dog is!", "Your dog is so cute."])
model = JumpStartModel(model_id=model_id)
predictor = model.deploy()
response = predictor.predict(endpoint_input)
prin... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=intfloat%2Fe5-large-v2&smModelId=huggingface-sentencesimilarity-e5-large-v2&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=intfloat%2Fe5-large-v2&smModelId=huggingface-sentencesimilarity-e5-large-v2&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
intfloat/multilingual-e5-base | huggingface-sentencesimilarity-multilingual-e5-base | false | true | true | true | false | from sagemaker.jumpstart.model import JumpStartModel
import json
model_id = "huggingface-sentencesimilarity-multilingual-e5-base"
endpoint_input = json.dumps(["How cute your dog is!", "Your dog is so cute."])
model = JumpStartModel(model_id=model_id)
predictor = model.deploy()
response = predictor.predict(endpoint_in... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=intfloat%2Fmultilingual-e5-base&smModelId=huggingface-sentencesimilarity-multilingual-e5-base&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=intfloat%2Fmultilingual-e5-base&smModelId=huggingface-sentencesimilarity-multilingual-e5-base&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
intfloat/multilingual-e5-large | huggingface-sentencesimilarity-multilingual-e5-large | false | true | true | true | false | from sagemaker.jumpstart.model import JumpStartModel
import json
model_id = "huggingface-sentencesimilarity-multilingual-e5-large"
endpoint_input = json.dumps(["How cute your dog is!", "Your dog is so cute."])
model = JumpStartModel(model_id=model_id)
predictor = model.deploy()
response = predictor.predict(endpoint_i... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=intfloat%2Fmultilingual-e5-large&smModelId=huggingface-sentencesimilarity-multilingual-e5-large&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=intfloat%2Fmultilingual-e5-large&smModelId=huggingface-sentencesimilarity-multilingual-e5-large&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
lighteternal/nli-xlm-r-greek | huggingface-zstc-lighteternal-nli-xlm-r-greek | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model_id = "huggingface-zstc-lighteternal-nli-xlm-r-greek"
endpoint_input = {'sequences': 'one d... | [{"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com/sagemaker/jumpstart"}] | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=lighteternal%2Fnli-xlm-r-greek&smModelId=huggingface-zstc-lighteternal-nli-xlm-r-greek&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
meta-llama/Llama-2-13b-chat-hf | meta-textgeneration-llama-2-13b-f | false | true | true | true | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="meta-textgeneration-llama-2-13b-f")
example_payloads = model.re... | [{"label": "Large Language Model (LLM): Run Inference in Amazon SageMaker JumpStart", "href": "https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart-foundation-models/text-generation-chatbot.ipynb"}, {"label": "Amazon SageMaker JumpStart", "href": "https://aws.amazon.com... | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=meta-llama%2Fllama-2-13b-chat-hf&smModelId=meta-textgeneration-llama-2-13b-f&hasVariants=false&page=deploy | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=meta-llama%2Fllama-2-13b-chat-hf&smModelId=meta-textgeneration-llama-2-13b-f&supportServerless=false&supportServerful=true&hasVariants=false&page=customize | null | null | null | null | null | null | null | null | null |
meta-llama/Llama-2-13b-hf | null | false | null | true | false | null | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="meta-textgeneration-llama-2-13b")
example_payloads = model.retr... | [{"href": "https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart-foundation-models/llama-2-text-completion.ipynb", "label": "Large Language Model (LLM): Run Inference in Amazon SageMaker JumpStart"}, {"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon... | null | null | null | null | null | null | null | null | null | null | null | null | null |
meta-llama/Llama-2-70b-chat-hf | meta-textgenerationneuron-llama-2-70b-f | false | false | true | false | false | # SageMaker JumpStart provides APIs as part of SageMaker SDK that allow you to deploy and fine-tune models in network isolation using scripts that SageMaker maintains.
from sagemaker.jumpstart.model import JumpStartModel
model = JumpStartModel(model_id="meta-textgeneration-llama-2-70b-f")
example_payloads = model.re... | [{"href": "https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart-foundation-models/text-generation-chatbot.ipynb", "label": "Large Language Model (LLM): Run Inference in Amazon SageMaker JumpStart"}, {"href": "https://aws.amazon.com/sagemaker/jumpstart", "label": "Amazon... | null | null | https://console.aws.amazon.com/sagemaker/home#/launch?source=hf&extModelId=meta-llama%2Fllama-2-70b-chat-hf&smModelId=meta-textgenerationneuron-llama-2-70b-f&hasVariants=false&page=deploy | null | null | null | null | null | null | null | null | null | null |
Subsets and Splits
Serverless Deployable Models
Filters for models that support all three deployment configurations (deployable, serverful training, and serverless customization) to identify models suitable for flexible deployment scenarios.