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๐ค Optimum Neuron Model Exporter ๐๏ธ
This Space allows you to automatically export ๐ค transformers to AWS Neuron-optimized format for Inferentia/Trainium acceleration.
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Pipeline Type
Task (auto can infer from model)
Model export in progress...
optimum-neuron version: 0.4.1
This Space allows you to automatically export ๐ค transformers to AWS Neuron-optimized format for Inferentia/Trainium acceleration.
Simply provide a model ID from the Hugging Face Hub, and choose your desired output.
โจ Key Features
- ๐ Create a New Optimized Repo: Automatically converts your model and uploads it to a new repository under your username (e.g.,
your-username/model-name-neuron). - ๐ Link Back to Original: Creates a Pull Request on the original model's repository to add a link to your optimized version, making it easier for the community to discover.
- ๐ ๏ธ PR to a Custom Repo: For custom workflows, you can create a Pull Request to add the optimized files directly into an existing repository you own.
- ๐ฆ Contribute to Cache: Contribute the generated compilation artifacts to a centralized cache repository (or your own private cache), helping avoid recompilation of already exported models.
โ๏ธ How to Use
- Model ID: Enter the ID of the model you want to export (e.g.,
bert-base-uncasedorstabilityai/stable-diffusion-xl-base-1.0) and choose the corresponding task. - Export Options: Select at least one option for where to save the exported model. You can provide your own cache repo ID or use the default (
aws-neuron/optimum-neuron-cache). - Convert & Upload: Click the button and follow the logs to track progress!
๐จ Task Categories Legend
Feature Extraction
NLP
Text Generation
Audio
Vision
Multimodal
Similarity
๐ค Transformers
| Architecture | Supported Tasks |
|---|---|
| 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 |
| BLOOM | text-generation |
| 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 |
| GPT2 | text-generation |
| Hubert | feature-extraction automatic-speech-recognition audio-classification |
| Levit | feature-extraction image-classification |
| Llama, Llama 2, Llama 3 | text-generation |
| Mistral | 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 |
| OPT | text-generation |
| Phi | feature-extraction text-classification token-classification |
| 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 |
| 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 |
๐งจ Diffusers
| Architecture | Supported Tasks |
|---|---|
| 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-ฮฑ | text-to-image |
| PixArt-ฮฃ | text-to-image |
| Flux | text-to-image |
๐ค Sentence Transformers
| Architecture | Supported Tasks |
|---|---|
| Transformer | feature-extraction sentence-similarity |
| CLIP | feature-extraction zero-shot-image-classification |
๐ก Note: Some architectures may have specific requirements or limitations. DeBERTa models are only supported on INF2 instances.
For more details, check the Optimum Neuron documentation.