LiquidAI/d1-omni-600M
image-text-to-text model by LiquidAI
From the publisher
Model card & documentation
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d1-omni-600M is a 600M parameter decision model built on LFM2.5-Encoder-350M. You give it a state (text or JSON, with images or a voice clip) and a set of named questions. It returns typed answers with zero output tokens: every answer is read directly from the model's distribution over the options, with no generation and no parsing. 112M audio encoder. Every modality runs the same trunk weights. Find more information about open d1 in our blog post. text is cut to 896 tokens, as trained We recommend d1-omni-600M wherever a pipeline needs a yes/no, a pick from named options, or a rating: routing and triage, moderation, intent and topic classification, voice-command routing, extraction checks, reranking, agent guardrails, and visual inspection. It is not a chat model and does not write text. Install the dependencies (requires transformers>=5.15): The model ships its own code, so load it with trustremotecode=True: A state is a…
Read the full model card ↗ · Preview checked 2026-10-08T09:37:16.445Z
Inside the original model card — Document outline
- d1-omni-600M
- 🗒️ Model Details
- 🏃 How to use
- Questions and answers
- ⚡ Speed
- 📊 Performance
- Decision Index 0.2.1
- Benchmarks as decisions
- 📬 Contact
- Citation
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Model overview
LiquidAI/d1-omni-600M is a image-text-to-text model repository published by LiquidAI on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- image-text-to-text
- Library
- transformers
- Recent downloads (30 days)
- 28
- Cumulative likes
- 52
- Hugging Face trending score
- 52
- Reported safetensors parameters
- 587,161,089
- Architecture
- D1OmniModel
- License
- other
- Access
- Not gated by Hugging Face
- Created
- 2026-10-05T17:18:48.000Z
- Last modified
- 2026-10-07T20:22:38.000Z
Compatibility and lineage
Reported languages: en, de, es, fr, it, nl, pl, pt, ar, hi, ja, ru, tr, vi, zh
Reported base models: LiquidAI/LFM2.5-Encoder-350M
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-08T06:39:12.727Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.