{"schema_version":"onlylabs.public_signal.v1","title":"ByteDance (Doubao/Seed) Model: ByteDance-Seed/ConfRover-interp-20M-v1.0","description":"ByteDance (Doubao/Seed) model signal with public source context, captured evidence pages, related signals, and data-business radar classification.","url":"https://onlylabs.fyi/signals/0c4465f9-3bd7-4228-b265-9c602877702d","json_url":"https://onlylabs.fyi/signals/0c4465f9-3bd7-4228-b265-9c602877702d/signal.json","generated_at":"2026-06-11T02:49:49.911395+00:00","org":{"slug":"bytedance","name":"ByteDance (Doubao/Seed)","category":"frontier-lab","category_label":"Frontier lab","dossier_url":"https://onlylabs.fyi/labs/bytedance","dossier_json_url":"https://onlylabs.fyi/labs/bytedance/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/0c4465f9-3bd7-4228-b265-9c602877702d","signal_json":"https://onlylabs.fyi/signals/0c4465f9-3bd7-4228-b265-9c602877702d/signal.json","source":"https://huggingface.co/ByteDance-Seed/ConfRover-interp-20M-v1.0","lab_dossier":"https://onlylabs.fyi/labs/bytedance","lab_dossier_json":"https://onlylabs.fyi/labs/bytedance/dossier.json","analysis":"https://onlylabs.fyi/analysis/bytedance","analysis_json":"https://onlylabs.fyi/analysis/bytedance/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/bytedance/evidence.json","category":"https://onlylabs.fyi/frontier","category_json":"https://onlylabs.fyi/frontier.json","category_feed":"https://onlylabs.fyi/frontier/feed.xml","category_signals_json":"https://onlylabs.fyi/signals.json","topic":"https://onlylabs.fyi/topics/releases","topic_signals_json":"https://onlylabs.fyi/topics/releases/signals.json","topic_feed":"https://onlylabs.fyi/topics/releases/feed.xml","data_business":null},"answer_pack":{"answer":"ByteDance (Doubao/Seed) published ByteDance-Seed/ConfRover-interp-20M-v1.0. 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It leverages diffusion probability model to learn the distribution of protein 3D conformations and captures the their temporal dependencies between frames through temporal causal transformers. Models are trained using molecular dynamics (MD) trajectories data and can generate protein conformation ensembles and motion trajectories conditioned on the input protein amino acid sequence. This variant was continued trained from the base model with additional conformation interpolation task. **Basic info** | Model ID | ConfRover-interp-20M-v1.0 | |:--|:--| | **Variant** | interp | | **Size** | 20M | | **Version** | v1.0 | | **Recommend** | For interpolation tasks | | **License** | Apache-2.0 | Model Sources <!-- Provide the basic links for the model. --> - **Repository:**..."},"evidence_pages":[{"url":"https://huggingface.co/ByteDance-Seed/ConfRover-interp-20M-v1.0/raw/main/README.md","final_url":"https://huggingface.co/ByteDance-Seed/ConfRover-interp-20M-v1.0/raw/main/README.md","title":"ByteDance-Seed/ConfRover-interp-20M-v1.0 model card","http_status":200,"content_type":"text/plain; charset=utf-8","capture_method":"plain","fetched_at":"2026-06-11T02:49:49.911395+00:00","bytes":3667,"raw_path":"619c01e42f26ff6d8a4951442471c0e054003754fc82b42162f6e5069ff5d382.md","content_hash":"7f5d6036f39d35225a30854e2669b9f01ad713b8ccaaaeac380eb23b1feb95e6","excerpt_chars":1200,"truncated":true,"excerpt":"--- license: apache-2.0 pipeline_tag: other library_name: confrover --- Model Card for `ConfRover-interp-20M-v1.0` <!-- Provide a quick summary of what the model is/does. --> ConfRover base model trained for conformation interpolation Model Details Model Description <!-- Provide a longer summary of what this model is. --> ConfRover is a deep generative model for protein 3D conformation and motion dynamics. It leverages diffusion probability model to learn the distribution of protein 3D conformations and captures the their temporal dependencies between frames through temporal causal transformers. Models are trained using molecular dynamics (MD) trajectories data and can generate protein conformation ensembles and motion trajectories conditioned on the input protein amino acid sequence. 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