Training on AWS Trainium instances (Trn1) enables large-scale model training with distributed parallelism strategies.
Requirements:
The following architectures have custom modeling implementations with distributed training support:
| Architecture | Task | Tensor Parallelism | Pipeline Parallelism |
|---|---|---|---|
| Llama, Llama 2, Llama 3 | text-generation | ✓ | ✓ |
| Qwen3 | text-generation | ✓ | ✓ |
| Granite | text-generation | ✓ | ✗ |
If you need to add support for a custom model not listed above, check out our contribute for training guide to learn how to implement custom modeling with distributed training support. You can also open an issue in the Optimum Neuron GitHub repository to request support for it.
The following table lists the architectures and tasks that Optimum Neuron supports for inference on Amazon EC2 Inf2 instances.
If a LLM is listed, e.g. a model with a
text-generationtask, it means that there is also TGI support for it.
| Architecture | Task |
|---|---|
| ALBERT | feature-extraction, fill-mask, multiple-choice, question-answering, text-classification, token-classification |
| AST | feature-extraction, audio-classification |
| BERT | feature-extraction, fill-mask, multiple-choice, question-answering, text-classification, token-classification |
| Beit | feature-extraction, image-classification |
| CamemBERT | feature-extraction, fill-mask, multiple-choice, question-answering, text-classification, token-classification |
| CLIP | feature-extraction, image-classification |
| ConvBERT | feature-extraction, fill-mask, multiple-choice, question-answering, text-classification, token-classification |
| ConvNext | feature-extraction, image-classification |
| ConvNextV2 | feature-extraction, image-classification |
| CvT | feature-extraction, image-classification |
| DeBERTa (INF2 only) | feature-extraction, fill-mask, multiple-choice, question-answering, text-classification, token-classification |
| DeBERTa-v2 (INF2 only) | feature-extraction, fill-mask, multiple-choice, question-answering, text-classification, token-classification |
| Deit | feature-extraction, image-classification |
| DistilBERT | feature-extraction, fill-mask, multiple-choice, question-answering, text-classification, token-classification |
| DonutSwin | feature-extraction |
| Dpt | feature-extraction |
| ELECTRA | feature-extraction, fill-mask, multiple-choice, question-answering, text-classification, token-classification |
| ESM | feature-extraction, fill-mask, text-classification, token-classification |
| FlauBERT | feature-extraction, fill-mask, multiple-choice, question-answering, text-classification, token-classification |
| Granite | text-generation |
| Hubert | feature-extraction, automatic-speech-recognition, audio-classification |
| Levit | feature-extraction, image-classification |
| Llama, Llama 2, Llama 3 | text-generation |
| Llama 4 | text-generation |
| Mixtral | text-generation |
| MobileBERT | feature-extraction, fill-mask, multiple-choice, question-answering, text-classification, token-classification |
| MobileNetV2 | feature-extraction, image-classification, semantic-segmentation |
| MobileViT | feature-extraction, image-classification, semantic-segmentation |
| ModernBERT | feature-extraction, fill-mask, text-classification, token-classification |
| MPNet | feature-extraction, fill-mask, multiple-choice, question-answering, text-classification, token-classification |
| Phi3 | text-generation |
| Phi | feature-extraction, text-classification, token-classification |
| Qwen2, Qwen3, Qwen3Moe | text-generation |
| RoBERTa | feature-extraction, fill-mask, multiple-choice, question-answering, text-classification, token-classification |
| RoFormer | feature-extraction, fill-mask, multiple-choice, question-answering, text-classification, token-classification |
| SmolLM3 | text-generation |
| Swin | feature-extraction, image-classification |
| T5 | text2text-generation |
| UniSpeech | feature-extraction, automatic-speech-recognition, audio-classification |
| UniSpeech-SAT | feature-extraction, automatic-speech-recognition, audio-classification, audio-frame-classification, audio-xvector |
| ViT | feature-extraction, image-classification |
| Wav2Vec2 | feature-extraction, automatic-speech-recognition, audio-classification, audio-frame-classification, audio-xvector |
| WavLM | feature-extraction, automatic-speech-recognition, audio-classification, audio-frame-classification, audio-xvector |
| Whisper | automatic-speech-recognition |
| XLM | feature-extraction, fill-mask, multiple-choice, question-answering, text-classification, token-classification |
| XLM-RoBERTa | feature-extraction, fill-mask, multiple-choice, question-answering, text-classification, token-classification |
| Yolos | feature-extraction, object-detection |
| Architecture | Task |
|---|---|
| Stable Diffusion | text-to-image, image-to-image, inpaint |
| Stable Diffusion XL Base | text-to-image, image-to-image, inpaint |
| Stable Diffusion XL Refiner | image-to-image, inpaint |
| SDXL Turbo | text-to-image, image-to-image, inpaint |
| LCM | text-to-image |
| PixArt-α | text-to-image |
| PixArt-Σ | text-to-image |
| Flux | text-to-image, inpaint |
| Flux Kontext | text-to-image, image-to-image |
| Architecture | Task |
|---|---|
| Transformer | feature-extraction, sentence-similarity |
| CLIP | feature-extraction, zero-shot-image-classification |
To learn how to export a model for inference, you can check this guide.