Memulai Amazon SageMaker JumpStart
Ikhtisar
Amazon SageMaker JumpStart adalah hub machine learning (ML) yang dapat membantu Anda mempercepat perjalanan ML Anda. Jelajahi bagaimana Anda dapat memulai dengan algoritma bawaan dengan model yang dilatih sebelumnya dari hub model, model fondasi yang dilatih sebelumnya, dan solusi yang dibuat sebelumnya untuk menyelesaikan kasus penggunaan umum. Untuk memulai, lihat dokumentasi atau contoh buku catatan yang dapat Anda jalankan dengan cepat.
Total results: 567
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- Nama Model A-Z
- Nama Model Z-A
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foundation model
FeaturedText GenerationMeta-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 GenerationMeta-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 GenerationMeta-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 GenerationMeta-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 GenerationMeta 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 GenerationMeta 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 LanguageMeta 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 GenerationLlama 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 GenerationLlama 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 GenerationLlama 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 GenerationLlama 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 GenerationLlama 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