LiquidAI/d1-3B
image-text-to-text model by LiquidAI
From the publisher
Model card & documentation
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d1-3B is a 3B parameter decision model built on LFM2.5-VL-3B. You give it a state (text, JSON, images, or a mix) and a set of questions. It returns calibrated, typed answers in one forward pass with zero output tokens. and of Decider 35B-A3B (47.11). (LFM2.5-VL-3B: 73.9). Find more information about open d1 in our blog post. d1-3B is a multimodal decision model with the following features: We recommend d1-3B wherever a pipeline needs a yes/no, a pick from named options, or a rating: routing and triage, moderation, intent and topic classification, extraction checks, reranking, LLM-as-a-judge scoring, agent guardrails, and visual inspection. It is not a chat model and does not write text. Install the dependencies (requires transformers>=5.14): The model ships its own code, so load it with trustremotecode=True: A state is a string, any JSON value, or None when the images are the whole state. Questions follow the Decision Index…
Read the full model card ↗ · Preview checked 2026-10-08T09:35:20.736Z
Inside the original model card — Document outline
- d1-3B
- 🗒️ Model Details
- 🏃 How to use
- Questions and answers
- ⚡ Speed
- Edge Inference
- GPU Inference
- 📊 Performance
- Decision Index 0.2.1
- Benchmarks as decisions
- Vision
- 📬 Contact
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Model overview
LiquidAI/d1-3B 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)
- 15
- Cumulative likes
- 116
- Hugging Face trending score
- 116
- Reported safetensors parameters
- 3,123,483,888
- Architecture
- Lfm2VlForConditionalGeneration
- License
- other
- Access
- Not gated by Hugging Face
- Created
- 2026-10-05T09:55:28.000Z
- Last modified
- 2026-10-07T20:23:00.000Z
Compatibility and lineage
Reported languages: ar, zh, en, fr, de, hi, id, it, ja, ko, pl, pt, ru, es, th, vi
Reported base models: LiquidAI/LFM2.5-VL-3B
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.