{"schema_version":"onlylabs.public_signal.v1","title":"ByteDance (Doubao/Seed) Model: ByteDance-Seed/byteff2","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/d9458cfe-645c-4193-91a6-ac50aacdb946","json_url":"https://onlylabs.fyi/signals/d9458cfe-645c-4193-91a6-ac50aacdb946/signal.json","generated_at":"2026-06-11T02:50:36.487437+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/d9458cfe-645c-4193-91a6-ac50aacdb946","signal_json":"https://onlylabs.fyi/signals/d9458cfe-645c-4193-91a6-ac50aacdb946/signal.json","source":"https://huggingface.co/ByteDance-Seed/byteff2","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/byteff2. 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ByteFF-Pol achieves exceptional accuracy in predicting the thermodynamic and transport properties of small-molecule liquids and electrolytes, outperforming SOTA traditional and ML force fields Trained Models The `trained_models` folder contains the trained model for ByteFF-Pol and its corresponding configuration (.yaml) file. How to use Code and examples are available in the [byteff2](https://github.com/ByteDance-Seed/byteff2) repository. Citation If you find ByteFF-Pol is useful for your research and applications, feel free to give us a star ⭐ or cite us using: ```bibtex @misc{zheng2025bridgingquantummechanicsorganic, title = {Bridging Quantum Mechanics to Organic Liquid Properties via a Universal Force Field}, author..."},"evidence_pages":[{"url":"https://huggingface.co/ByteDance-Seed/byteff2/raw/main/README.md","final_url":"https://huggingface.co/ByteDance-Seed/byteff2/raw/main/README.md","title":"ByteDance-Seed/byteff2 model card","http_status":200,"content_type":"text/plain; charset=utf-8","capture_method":"plain","fetched_at":"2026-06-11T02:50:36.487437+00:00","bytes":1551,"raw_path":"f404901c005f1c1a41059d747f371d679b3f1f18dfa5d2738ec165d24c7cce1e.md","content_hash":"d326e933834089ad05453620eced221eb3bae4fac6bc6d5524218870331dd0c8","excerpt_chars":1200,"truncated":true,"excerpt":"--- license: cc-by-nc-4.0 tags: - chemistry - biology --- ByteFF2 This repository contains the model used for the paper [Bridging Quantum Mechanics to Organic Liquid Properties via a Universal Force Field](https://arxiv.org/abs/2508.08575)。 [ByteFF-Pol](https://arxiv.org/abs/2508.08575) is a polarizable force field parameterized by a graph neural network (GNN), trained on high-level quantum mechanics (QM) data, thus eliminating the need for experimental calibration. 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