Inizia a usare Amazon SageMaker JumpStart
Panoramica
Amazon SageMaker JumpStart è un hub di machine learning (ML) che può contribuire ad accelerare il percorso verso il ML. Scopri come iniziare a utilizzare algoritmi integrati con modelli preaddestrati provenienti da hub di modelli, modelli di base preformati e soluzioni predefinite per risolvere casi d'uso comuni. Per iniziare, consulta la documentazione o i notebook di esempio che puoi eseguire rapidamente.
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Total results: 582
Total results: 582
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foundation model
FeaturedText Generation
Meta-Llama-3-70B-Instruct
Meta70B instruction tuned variant of Llama 3 models. Llama 3 uses a decoder-only transformer architecture and new tokenizer that provides improved model performance.Fine-tunable -
foundation model
FeaturedText Generation
Meta-Llama-3.1-405B-FP8
Meta405B variant of Llama 3.1 models. Llama 3.1 uses a decoder-only transformer architecture and new tokenizer that provides improved model performance.Fine-tunable -
foundation model
FeaturedText Generation
Meta-Llama-3.1-8B-Instruct
Meta8B instruction tuned variant of Llama 3.1 models. Llama 3.1 uses a decoder-only transformer architecture and new tokenizer that provides improved model performance.Fine-tunable -
foundation model
FeaturedText Generation
Meta-Llama-3.1-70B-Instruct
Meta70B instruction tuned variant of Llama 3.1 models. Llama 3.1 uses a decoder-only transformer architecture and new tokenizer that provides improved model performance.Fine-tunable -
foundation model
FeaturedText Generation
Meta Llama 3.2 3B Instruct
Meta3B instruction tuned variant of Llama 3.2 models. Llama 3.2 uses a decoder-only transformer architecture and new tokenizer that provides improved model performance.Fine-tunable -
foundation model
FeaturedText Generation
Meta Llama 3.2 1B Instruct
Meta1B instruction tuned variant of Llama 3.2 models. Llama 3.2 uses a decoder-only transformer architecture and new tokenizer that provides improved model performance.Fine-tunable -
foundation model
FeaturedVision Language
Meta Llama 3.2 11B Vision Instruct
Meta11b instruction-tuned variants of Llama 3.2 models that supports both text and image as input.Deploy only -
foundation model
FeaturedText Generation
Llama 2 13B
Meta13B variant of Llama 2 models. Llama 2 is an auto-regressive language model that uses an optimized transformer architecture. Llama 2 is intended for commercial and research use in English. It comes in a range of parameter sizes—7 billion, 13 billion, and 70 billion—as well as pre-trained and fine-tuned variations.Fine-tunable -
foundation model
FeaturedText Generation
Llama 3
MetaLlama three from Meta comes in two parameter sizes — 8B and 70B with 8k context length — that can support a broad range of use cases with improvements in reasoning, code generation, and instruction following.
Deploy Only -
foundation model
FeaturedText Generation
Llama 2 70B
Meta70B variant of Llama 2 models. Llama 2 is an auto-regressive language model that uses an optimized transformer architecture. Llama 2 is intended for commercial and research use in English. It comes in a range of parameter sizes—7 billion, 13 billion, and 70 billion—as well as pre-trained and fine-tuned variations.Fine-tunable -
foundation model
FeaturedText Generation
Llama 2 7B
Meta7B variant of Llama 2 models. Llama 2 is an auto-regressive language model that uses an optimized transformer architecture. Llama 2 is intended for commercial and research use in English. It comes in a range of parameter sizes—7 billion, 13 billion, and 70 billion—as well as pre-trained and fine-tuned variations.Fine-tunable -
foundation model
FeaturedText Generation
Llama 2 70B Chat
Meta70B dialogue use case optimized variant of Llama 2 models. Llama 2 is an auto-regressive language model that uses an optimized transformer architecture. Llama 2 is intended for commercial and research use in English. It comes in a range of parameter sizes—7 billion, 13 billion, and 70 billion—as well as pre-trained and fine-tuned variations.Fine-tunable