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Optimum RBLN

Optimum RBLN은 허깅페이스 transformers와 diffusers 모델들이 RBLN NPU, 즉 ATOM (RBLN-CA02) 및 ATOM+ (RBLN-CA12)에서 실행 될 수 있도록 연결해주는 라이브러리 입니다. 이를 통해 허깅페이스 모델들의 다양한 다운스트림 태스크들을 단일 및 다중 NPU (Rebellions Scalable Design)에서 손쉽게 컴파일 및 추론 할 수 있습니다. 다음 표에 현재 Optimum RBLN이 지원하는 모델 목록이 나열되어 있습니다.

Transformers

Single NPU

| Model | Model Architecture | Task | | :---: | :-----------------------------: | :-----: | | Phi-2 | PhiForCausalLM | | | Gemma-2b | GemmaForCausalLM | | | GPT2 | GPT2LMHeadModel | | | GPT2-medium | GPT2LMHeadModel | | | GPT2-large | GPT2LMHeadModel | | | GPT2-xl | GPT2LMHeadModel | | | T5-small | T5ForConditionalGeneration | | | T5-base | T5ForConditionalGeneration | | | T5-large | T5ForConditionalGeneration | | | T5-3b | T5ForConditionalGeneration | | | BART-base | BartForConditionalGeneration | | | BART-large | BartForConditionalGeneration | | | KoBART-base | BartForConditionalGeneration | | | E5-base-4K | BertModel | | | LaBSE | BertModel | | | KR-SBERT-V40K-klueNLI-augSTS | BertModel | | | BERT-base | - BertForMaskedLM
- BertForQuestionAnswering | | | BERT-large | - BertForMaskedLM
- BertForQuestionAnswering | | | DistilBERT-base | DistilBertForQuestionAnswering | | | SecureBERT | RobertaForMaskedLM | | | RoBERTa | RobertaForSequenceClassification | | | BGE-M3 | XLMRobertaModel | | | BGE-Reranker-V2-M3 | XLMRobertaForSequenceClassification | | | BGE-Reranker-Base | XLMRobertaForSequenceClassification | | | BGE-Reranker-Large | XLMRobertaForSequenceClassification | | | Ko-Reranker | XLMRobertaForSequenceClassification | | | Whisper-tiny | WhisperForConditionalGeneration | | | Whisper-base | WhisperForConditionalGeneration | | | Whisper-small | WhisperForConditionalGeneration | | | Whisper-medium | WhisperForConditionalGeneration | | | Whisper-large-v3 | WhisperForConditionalGeneration | | | Whisper-large-v3-turbo | WhisperForConditionalGeneration | | | Wav2Vec2 | Wav2Vec2ForCTC | | | Audio-Spectogram-Transformer | ASTForAudioClassification | | | DPT-large | DPTForDepthEstimation | | | ViT-large | ViTForImageClassification | | | ResNet50 | ResNetForImageClassification | |

Multi-NPU

Note

다중 NPU 기능은 ATOM+ (RBLN-CA12)에서만 지원됩니다. 지금 사용 중인 NPU의 종류는 rbln-stat 명령어로 확인할 수 있습니다.

| Model | Model Architecture | Recommended # of NPUs | Task | | :---: | :-----------------------------: | :-----: | :-----: | | DeepSeek-R1-Distill-Llama-8b | LlamaForCausalLM | 8 | | | DeepSeek-R1-Distill-Llama-70b | LlamaForCausalLM | 16 | | | DeepSeek-R1-Distill-Qwen-1.5b | Qwen2ForCausalLM | 8 | | | DeepSeek-R1-Distill-Qwen-7b | Qwen2ForCausalLM | 8 | | | DeepSeek-R1-Distill-Qwen-14b | Qwen2ForCausalLM | 8 | | | DeepSeek-R1-Distill-Qwen-32b | Qwen2ForCausalLM | 16 | | | Llama3.3-70b | LlamaForCausalLM | 16 | | | Llama3.2-3b | LlamaForCausalLM | 8 | | | Llama3.1-70b | LlamaForCausalLM | 16 | | | Llama3.1-8b | LlamaForCausalLM | 8 | | | Llama3-8b | LlamaForCausalLM | 4 | | | Llama3-8b + LoRA | LlamaForCausalLM | 4 | | | Llama2-7b | LlamaForCausalLM | 4 | | | Llama2-13b | LlamaForCausalLM | 8 | | | Gemma-7b | GemmaForCausalLM | 4 | | | Mistral-7b | MistralForCausalLM | 4 | | | Qwen2-7b | Qwen2ForCausalLM | 4 | | | Qwen2.5-7b | Qwen2ForCausalLM | 4 | | | Qwen2.5-14b | Qwen2ForCausalLM | 8 | | | Salamandra-7b | LlamaForCausalLM | 4 | | | KONI-Llama3.1-8b | LlamaForCausalLM | 8 | | | EXAONE-3.0-7.8b | ExaoneForCausalLM | 4 | | | EXAONE-3.5-2.4b | ExaoneForCausalLM | 4 | | | EXAONE-3.5-7.8b | ExaoneForCausalLM | 8 | | | Mi:dm-7b | MidmLMHeadModel | 4 | | | SOLAR-10.7b | LlamaForCausalLM | 8 | | | EEVE-Korean-10.8b | LlamaForCausalLM | 8 | | | Llava-v1.6-mistral-7b | LlavaNextForConditionalGeneration | 4 | |

Diffusers

Note

윗 첨자 †가 표시된 모델은 크기가 커서 ATOM 하나에 담을 수 없습니다. 따라서 모델의 모듈들을 여러 개의 ATOM에 나누어 올려야합니다. 모델 모듈의 구체적인 분산 정보는 모델 예제 코드를 참조하십시오.

| Model | Model Architecture | Task | | :---: | :-----------------------------: | :-----: | | Stable Diffusion |
  • StableDiffusionPipeline
  • StableDiffusionImg2ImgPipeline
  • StableDiffusionInpaintPipeline
| | | Stable Diffusion + LoRA |
  • StableDiffusionPipeline
| | | Stable Diffusion V3† |
  • StableDiffusion3Pipeline
  • StableDiffusion3Img2ImgPipeline
  • StableDiffusion3InpaintPipeline
| | | Stable Diffusion XL |
  • StableDiffusionXLPipeline
  • StableDiffusionXLImg2ImgPipeline
  • StableDiffusionXLInpaintPipeline
| | | Stable Diffusion XL + multi-LoRA |
  • StableDiffusionXLPipeline
| | | SDXL-turbo |
  • StableDiffusionXLPipeline
  • StableDiffusionXLImg2ImgPipeline
| | | Stable Diffusion + ControlNet |
  • StableDiffusionControlNetPipeline
  • StableDiffusionControlNetImg2ImgPipeline
| | | Stable Diffusion XL + ControlNet |
  • StableDiffusionXLControlNetPipeline
  • StableDiffusionXLControlNetImg2ImgPipeline
| | | Kandinsky V2.2 |
  • KandinskyV22InpaintCombinedPipeline
  • KandinskyV22PriorPipeline
  • KandinskyV22InpaintPipeline
| |