ATTRIBUTIONS.md

# VisionPsy-Nano: State-of-the-Art On-Device Vision-Language Models

## KEY HIGHLIGHTS

- **Compact VLMs built for the edge:** Tether AI Research introduces VisionPsy-Nano, a family of compact (~460M-parameter) vision-language models (VLMs) purpose-built for on-device and edge deployment. It ships as two variants: **VisionPsy-Nano-460M** (tuned for quality) and **VisionPsy-Nano-460M-Flash** (tuned for latency), bringing multimodal understanding that used to require the cloud onto the phone in your pocket.
- **Best-in-class at ~0.5B:** VisionPsy-Nano-460M compares favorably to every other ~0.5B VLM tested, including LFM2.5-VL-450M, SmolVLM2-500M, and its own nanoVLM-460M-8k base, on **16 of 17 benchmarks**, with a leading overall normalized score of **62.3** (vs 59.6 / 52.5 / 54.9).
- **Leads every capability category:** VisionPsy-Nano-460M tops all four categories: document understanding & OCR, visual perception, reasoning & knowledge, and instruction following & reliability. Its widest relative margins are in reasoning & knowledge (**+7.4%** over the next-best ~0.5B model) and visual perception (**+4.6%**).
- **Punches above its weight:** In the Instruction Following & Reliability category, covering both MM-IFEval (42.3) and POPE (87.9), VisionPsy-Nano-460M outperforms models 1.6x to 2.3x its size: FastVLM-0.5B (759M), Qwen3.5-0.8B (873M), and InternVL3.5-1B (1061M).
- **Flash is an order of magnitude faster on real phones:** By using far fewer visual tokens, VisionPsy-Nano-460M-Flash reaches the first token **~19–23x** faster than nanoVLM-460M-8k and SmolVLM2-500M on Pixel 9, Galaxy S23, and Galaxy S25 Ultra, and up to **~36x** on iPhone 15. It also stays ahead of the faster competitors, reaching the first token **~1.3–2.4x** faster than LFM2.5-VL-450M and **~2.3–3.5x** faster than Qwen3.5-0.8B across all four devices, while retaining **~99%** of the full model's quality (61.4 vs 62.3 normalized).
- **Ready to use:** To accelerate development and innovation, Tether AI Research is today publicly releasing both models with three inference paths: full-precision reference quality via Transformers (`from_pretrained`); on-device via GGUF quantized checkpoints that run on a phone through llama.cpp (one-line invocation); and vLLM for high-throughput server inference.
- **Open weights, reproducible evals:** Released under Apache 2.0 with open weights, these models are intended to support researchers and for educational purposes. Every model is scored under the same VLMEvalKit protocol, with eval configs and judge setup included, so anyone can reproduce the benchmark numbers.

---

## 🚀 VisionPsy-Nano on Hugging Face & GitHub

All VisionPsy-Nano models, GGUF weights, and resources in one place.

| Resource | What it is | Link |
| --- | --- | --- |
| 🏆 **VisionPsy-Nano-460M** | Quality-focused ~0.5B model. Leads its weight class in all four capability areas. | [Open the model card](https://huggingface.co/qvac/VisionPsy-Nano-460M) |
| ⚡ **VisionPsy-Nano-460M-Flash** | Efficiency-optimized sibling. Fastest TTFT in its class; ships as 4-bit GGUF. | [Open the model card](https://huggingface.co/qvac/VisionPsy-Nano-460M-Flash) |
| 📦 **GGUF weights** | Quantized (Q4_0) builds for on-device llama.cpp | [VisionPsy-Nano-460M-GGUFs](https://huggingface.co/qvac/VisionPsy-Nano-460M-GGUFs) · [VisionPsy-Nano-460M-Flash-GGUFs](https://huggingface.co/qvac/VisionPsy-Nano-460M-Flash-GGUFs) |
| 🧰 **Evaluation harness** | VLMEvalKit, used for all in-house scoring. VisionPsy support is under review upstream — see [PR #1613](https://github.com/open-compass/VLMEvalKit/pull/1613). | [open-compass/VLMEvalKit](https://github.com/open-compass/VLMEvalKit) |
| 🐙 **GitHub Repository** | Source code and inference scripts for VisionPsy Nano across Transformers, vLLM, and llama.cpp runtimes. | [tether-ai-research/qvac-visionpsy-nano](https://github.com/tether-ai-research/qvac-visionpsy-nano) |

---

## HEADLINE RESULTS

The two figures below summarize where VisionPsy-Nano-460M stands. All numbers are computed **in-house with a single [VLMEvalKit](https://github.com/open-compass/VLMEvalKit) [7] harness** so every model is scored identically, using each benchmark's **official metric** (accuracy for most; POPE = F1, MMVet = partial credit, MM-IFEval = instruction-following accuracy, MME = Perception + Reasoning, OCRBench = /1000). All LLM-as-judge scoring uses **Qwen3.6-27B [8]**.

**Best-in-class at ~0.5B.** VisionPsy-Nano-460M has the highest overall normalized score of any model in its ~0.5B weight class, and leads its cohort in every one of the four capability areas. Per-benchmark results across all 17 evaluations are in [Benchmarks](#benchmarks) below.

![Category averages vs similar-size VLMs](https://cdn-uploads.huggingface.co/production/uploads/6a512bc901d52eda49267fb8/vtA8hQ9m5nXHDkyF47KSt.png)


**Punching above its weight.** On three full benchmarks (ScienceQA, MM-IFEval, and POPE), it beats every one of the larger 0.75-1B models outright:

![Beating larger models on ScienceQA, MM-IFEval, POPE](https://cdn-uploads.huggingface.co/production/uploads/6a512bc901d52eda49267fb8/QaaBwIVHMfQS5WeYY_4WY.png)


---

## Introducing VisionPsy-Nano

**Tether Data, S.A. de C.V. (Tether AI Research, we, us, our)** presents
**VisionPsy-Nano**, a family of ~460M-parameter vision-language models that
achieve state-of-the-art results for their size on a comprehensive suite of
public benchmarks, while being purpose-built for edge deployment. The family
has two variants:

- **VisionPsy-Nano-460M:** the **best-quality** ~0.5B model, for when accuracy
  is the priority.
- **VisionPsy-Nano-460M-Flash:** the **best-latency** model, for when
  time-to-first-token and RAM are the binding constraints. Same
  weight class, radically fewer visual tokens.

---

## Why a 460M VLM

Vision-language models have advanced rapidly, but the best ones still live in the cloud. State-of-the-art open VLMs assume server-class GPUs with tens of gigabytes of memory, which conflicts with the privacy, latency, and offline-reliability needs of the places multimodal AI is most useful: a phone camera pointed at a document, a form, a chart, or a scene. The challenge is not only to make VLMs smaller; it is to make a *small* model that is genuinely accurate, responsive, and safe on the hardware people already carry.

On-device inference removes network round-trips, keeps images and documents on the user's device, and works offline, but it imposes a hard budget on parameters, memory, and latency. A phone typically exposes a small slice of RAM to a single app and has no dedicated VRAM, so a deployable VLM must be small *and* quantizable *and* fast to the first token. The dominant cost in a small VLM's prefill is the number of **visual tokens** the language backbone has to attend to, which is exactly the lever Flash pulls.

The current landscape forces a trade-off between quality and deployability. Models in the ~0.5B range (SmolVLM2-500M [2], the nanoVLM-460M base [3]) are deployable but leave significant accuracy on the table, particularly on reasoning, instruction following, and hallucination robustness. Slightly larger models (FastVLM-0.5B [4], Qwen3.5-0.8B [5], InternVL3.5-1B [6]) score higher on aggregate but cost more memory and are slower to first token, often dramatically so at high input resolution, where their visual-token counts balloon. VisionPsy-Nano was designed to close that gap.

---

## Architecture

VisionPsy-Nano is built on nanoVLM [3] (base checkpoint `lusxvr/nanoVLM-460M-8k`), a clean, compact VLM architecture that pairs a **SigLIP2** [9] vision encoder with a **SmolLM2** [10] language backbone through a lightweight pixel-shuffle connector. Building on nanoVLM lets us concentrate the parameter budget on a single image-text path rather than a large, general-purpose multimodal stack. Both variants are released under Apache 2.0 as float32 checkpoints for reference-quality inference, with quantized GGUF builds for on-device use.

VisionPsy-Nano is trained and optimized for **one image per query**. This is a deliberate scoping choice for the target use cases (camera Q&A, document/chart/scene understanding), and it lets the model spend its limited capacity on getting single-image understanding right rather than spreading it across multi-image reasoning.

The full and Flash models share the same architecture and trained behavior; Flash differs only in its visual token budget, which is reduced by preserving the native image scale before tiling. Efficiency is a property of the architecture, not the weights.

| Property | VisionPsy-Nano-460M | VisionPsy-Nano-460M-Flash |
| --- | --- | --- |
| Parameters | ~460M total | ~460M total |
| Vision encoder | SigLIP2 base, patch16, 512x512 | SigLIP2 base, patch16, 512x512 |
| Language backbone | SmolLM2-360M | SmolLM2-360M |
| Connector | pixel-shuffle MLP (64 img tokens / tile) | pixel-shuffle MLP, processed at native resolution, then tiled |
| Visual tokens @512x512 | 1088 (full) | **64** |
| Context length | 8,192 tokens | 8,192 tokens |

*Table 1. Model architecture and specification comparison.*

---

## How we trained it

Rather than simply scaling generic multimodal data, our central bet is that **targeted supervision on the model's actual failure modes**, plus **checkpoint merging** and **alignment**, matter more than raw data volume at this scale. This mirrors a broader trend in efficient post-training: curriculum-style SFT, model merging, and preference optimization each contribute a distinct, complementary improvement.

To find those failure modes, we built a failure-analysis framework with two complementary halves. A **passive** mining pass has the Stage 2 checkpoint answer every item in our training pool, scores the responses with rule-based checks and an LLM judge, and keeps only the hard, clean cases where the model answers incorrectly but the ground truth is entirely reliable. An **active** agentic harness hunts for weaknesses the training pool does not contain: a teacher VLM (Qwen3.6-27B [8]) repeatedly interrogates the student with realistic, user-style questions grounded in real images, grades each answer with the source image in view, and biases sampling toward the sources where the student is struggling. Over 300 rounds and ~18,000 probes it cataloged dozens of weaknesses, clustering into output-format failures, degenerate repetition, numeric reasoning, spatial reasoning, exhaustive extraction, and dense-numeral OCR. These clusters directly shaped the Stage 3 data mixture and motivated the replay training in Stage 5.

Starting from the nanoVLM-460M-8k [3] base, VisionPsy-Nano is produced by a **five-stage post-training pipeline** that combines supervised learning, checkpoint merging, and preference optimization:

![Figure 1. Post-training workflow](https://cdn-uploads.huggingface.co/production/uploads/6a512bc901d52eda49267fb8/et17KlkBuuEr_l_JIFhxd.png)

*Figure 1. Post-training workflow.*

1. **Stage 1: Generic SFT.** Broad supervised fine-tuning on **NVIDIA Nemotron-Image-Training-v3** [11], building wide multimodal coverage across documents, charts, diagrams, scenes, and scene-text. Samples whose images are perceptual-hash near-duplicates of held-out benchmarks are removed first.
2. **Stage 2: Capability-Targeted SFT.** Curated FineVision [12] and multimodal instruction-following data targeting OCR, documents, charts, formulas, spatial reasoning, and instruction following, complementing Nemotron's broad supervision while maintaining plain-answer, single-image training.
3. **Stage 3: Weakness-targeted finetuning.** A stronger teacher (Qwen3.6-27B [8]) distills verified, gold-anchored supervision from the mined failures. Because each mined item already carries a trusted answer, we keep that answer fixed and accept only teacher output that agrees with it. Mixed with real weakness-targeted data and replay, and trained with InfoSFT [13], this yields a set of capability specialists.
4. **Stage 4: Model merging.** The strongest specialists are merged with TIES-Merging [14], which trims each fine-tune, elects an agreed-upon sign per parameter, and averages only the aligned updates. Merging happens entirely in weight space, producing one ordinary checkpoint with the same architecture, parameter count, and inference cost as any individual run.
5. **Stage 5: Preference alignment with replay.** A final alignment stage with replay training to stop degenerate "doom-loop" repetition, fold in safety checks, and align responses more closely with human expectations.

This staging is important for compact edge models: broad SFT builds coverage, failure-driven SFT sharpens exactly the weak spots, merging stabilizes the result, and alignment fixes the behaviors (looping, unsafe or off-format answers) that pure imitation learning tends to leave behind.

---

## Reliability and safety

A doom loop is not simply a verbose answer. It occurs when the model enters a self-reinforcing repetition pattern, repeating a phrase, sentence, or formatting token until the generation limit is reached, often without producing an end-of-sequence token. These failures are easy to miss in multiple-choice and short-answer benchmarks, where generation ends before the loop can develop. Rather than relying on generic anti-repetition data, we mine preference pairs directly from the Stage 4 model: when the same prompt yields both a cleanly terminated response and a genuine loop, the former becomes the chosen response and the latter the rejected one. This same-prompt construction isolates the unwanted behavior without changing the task, answer style, or visual input. We train on these pairs with MPO [15], plus capability replay to protect instruction following, OCR, and visual reasoning.

| Model | Doom-Loop Rate |
| --- | --- |
| SmolVLM2-500M [2] | 1.52% (6/395) |
| LFM2.5-VL-450M [1] | 0.51% (2/395) |
| VisionPsy-Nano-460M | **0.25% (1/395)** |

*Table 2. Doom-loop rate on a 395-case stress test covering recipes and visual how-to questions, long STEM and chart reasoning, exhaustive lists, and structured outputs.*

Safety training combines carefully filtered examples from the public portion of PKU-SafeRLHF-V [16] with internally curated cases covering harmful requests, privacy, self-harm, fraud, visual prompt injection, and other deployment risks. The mixture also contains benign boundary cases that should be answered normally, because the objective is not blanket refusal but the correct decision to answer, safely assist, abstain, or refuse.

We then stress-test every checkpoint with a VLM-native red-teaming harness. Each model faces 288 adversarial cases spanning 8 vulnerability categories and 9 attack methods across two channels: image-borne attacks that render the harmful instruction directly into the image (FigStep [17], typographic overlay, prompt-in-image) and text-channel jailbreaks over a blank canvas (roleplay, prompt injection, Base64, ROT13, leetspeak, plain text). All attacks come from a fixed, curated bank, so the scan is fully reproducible.

Across the 288 cases, VisionPsy-Nano-460M passes 76.9%, against 65.9% for the nanoVLM-460M-8k base it started from and 61.9% for SmolVLM2-500M, so alignment adds 11 points of adversarial robustness over the base. LFM2.5-VL-450M is comparable at 79.0%, with most of that difference concentrated in PersonalSafety; on six of the eight categories the two models sit within one or two cases of each other at 36 cases per category.

![Figure 2. Safety red-teaming pass rates by vulnerability category](https://cdn-uploads.huggingface.co/production/uploads/6a512bc901d52eda49267fb8/tYmmD6gBkqbXKtajf0DHz.png)

*Figure 2. Safety red-teaming pass rates by vulnerability category.*

---

## Benchmarks

All numbers are computed in-house with a single VLMEvalKit [7] harness so every model is scored identically, using each benchmark's official metric: accuracy for most, POPE = F1, MMVet = partial credit, MM-IFEval = instruction-following accuracy, MME = Perception + Reasoning, OCRBench = Final Score (/1000). Each model is evaluated on its own full sample set, and all LLM-as-judge scoring uses Qwen3.6-27B [8]. Open-ended VQA benchmarks (ChartQA, TextVQA, DocVQA, InfoVQA, OCRBench) are notoriously sensitive to string-matching artifacts ("12%" vs "12 percent", paraphrases, units, formatting), so on those we report **LLM-judge / strict** pairs.

The changes we used for these numbers are currently under review in VLMEvalKit:

  - **VisionPsy model support**: [PR #1613](https://github.com/open-compass/VLMEvalKit/pull/1613)
  - **Opt-in LLM-judge rescoring for open-ended VQA benchmarks**: [PR #1602](https://github.com/open-compass/VLMEvalKit/pull/1602)
  - **MM-IFEval bug fix**: [PR #1601](https://github.com/open-compass/VLMEvalKit/pull/1601)
  - **LLM-judge bug fix**: [PR #1611](https://github.com/open-compass/VLMEvalKit/pull/1611)

  Until they are merged, you can reproduce the benchmarks by applying these PRs on top of
  [VLMEvalKit](https://github.com/open-compass/VLMEvalKit).

We group the 17 public benchmarks into four capability areas. **VisionPsy-Nano-460M leads its ~0.5B cohort in every one of them.** Scores are normalized to 0-100 (MME /2800, OCRBench /1000; percentages otherwise).

| Capability area | Benchmarks | VisionPsy-Nano-460M | LFM2.5-VL-450M [1] | SmolVLM2-500M [2] | nanoVLM-460M-8k [3] |
| --- | --- | --- | --- | --- | --- |
| Document Understanding & OCR | OCRBench, DocVQA, ChartQA, InfoVQA, TextVQA | **73.9** | 71.6 | 62.4 | 69.5 |
| Visual Perception | MME, SEEDBench, MMBench, RealWorldQA | **61.5** | 58.8 | 53.9 | 55.2 |
| Reasoning & Knowledge | ScienceQA, AI2D, MMStar, MMMU, MathVista, MMVet | **52.2** | 48.6 | 45.1 | 43.7 |
| Instruction Following & Reliability | MM-IFEval, POPE | **65.1** | 64.3 | 46.9 | 51.4 |

*Table 3. VisionPsy-Nano-460M is the best ~0.5B model in all four capability areas.*

Per benchmark, VisionPsy-Nano-460M wins 15 of the 17 rows outright against the full ~0.5B cohort. On MMMU it sits 0.2 points behind SmolVLM2-500M, within noise at this sample size, so it compares favorably on 16 of 17; MMVet, where LFM2.5-VL-450M leads by 3.7 points, is the one clear loss. Against LFM2.5-VL-450M alone, its closest competitor, it leads on 16 of 17. To confirm the lead is not an artifact of the judge, we re-scored both models with GPT-4o-mini and GPT-5-chat in place of Qwen3.6-27B. The trend and the margin in normalized score remain almost identical (62.3 / 61.6 / 62.9 for VisionPsy-Nano-460M against 59.6 / 58.7 / 60.1 for LFM2.5-VL-450M), with the same 16 of 17 win count under every judge.

![Figure 3. Per-benchmark performance by capability area](https://cdn-uploads.huggingface.co/production/uploads/6a512bc901d52eda49267fb8/hGdp7z3h60sFTFGlRq0go.png)

*Figure 3. Per-benchmark performance by capability area against the ~0.5B cohort.*

At roughly **half to two-thirds the parameters**, VisionPsy-Nano-460M still beats FastVLM-0.5B [4] (~0.75B), Qwen3.5-0.8B [5], and InternVL3.5-1B [6] **outright on 3 full benchmarks**, and on many specific capabilities even where the larger models win on aggregate.

| Capability | Benchmark | N | VisionPsy-Nano-460M | FastVLM-0.5B (759M) | Qwen3.5-0.8B (873M) | InternVL3.5-1B (1061M) |
| --- | --- | --- | --- | --- | --- | --- |
| Science & diagram reasoning | ScienceQA | 2017 | **86.5** | 84.7 | 71.6 | 79.7 |
| Visual instruction following | MM-IFEval | 400 | **42.3** | 21.1 | 36.9 | 33.6 |
| Hallucination robustness | POPE (F1) | 5127 | **87.9** | 86.5 | 87.3 | 86.0 |
| Spatial position reasoning | MME (position) | 60 | **85.0** | 75.0 | 63.3 | 73.3 |
| Irregular text recognition | OCRBench (subset) | 50 | **92.0** | 80.0 | 88.0 | 82.0 |
| Object localization | MMStar (L2) | 40 | **57.5** | 45.0 | 50.0 | 55.0 |

*Table 4. The first three rows are full benchmarks; the last three are subcategories within larger benchmarks. N gives the sample count in each case. The larger models win the raw 17-benchmark average (Qwen3.5-0.8B 66.1, InternVL3.5-1B 65.9 vs VisionPsy-Nano-460M 62.3), which is expected given the parameter gap. The narrower claim here is that a 460M model still leads all three on three complete benchmarks and on the specific skills below them.*

---

## Flash: efficiency on real devices

VisionPsy-Nano-460M's image pipeline resizes the longest image side to 2048 pixels before tiling. This policy is effective for high-resolution inputs, but is inefficient for smaller images: upsampling increases the number of tiles and visual tokens without adding new image content. We therefore derive **VisionPsy-Nano-460M-Flash** from VisionPsy-Nano-460M by retaining the same model architecture and training procedure, while changing the image preprocessing policy. Instead of normalizing all inputs to the backbone resolution, Flash processes images at their original size. Only images smaller than 512x512 are upscaled to this minimum resolution.

Flash trades a little accuracy for a large latency win by feeding the backbone a fraction of the visual tokens at the same input resolution, avoiding tokens spent on spatial detail introduced solely by interpolation. It does not use token pruning, token merging, or a learned compression module; the reduction follows directly from preserving the native image scale before tiling.

![Figure 4. Visual preprocessing in VisionPsy-Nano-460M and VisionPsy-Nano-460M-Flash](https://cdn-uploads.huggingface.co/production/uploads/6a512bc901d52eda49267fb8/swLLG1Is2OR97-SrdpPa6.png)

*Figure 4. Visual preprocessing in VisionPsy-Nano-460M (Nano) and VisionPsy-Nano-460M-Flash (Flash). Nano upsamples inputs to a longest side of 2048 before tiling, whereas Flash preserves the native resolution, with a minimum size of 512×512. This avoids unnecessary resolution inflation and yields a smaller number of visual tokens.*

### Visual token footprint

Flash often produces the shortest visual sequence, with the largest gains observed for low-resolution inputs. For a native 512x512 image, Flash uses 64 tokens, compared with 256 for LFM2.5-VL [1] and Qwen3.5 [5], and 1088 for nanoVLM [3] and SmolVLM2 [2], corresponding to a **4×–17× reduction**. The advantage remains across larger and non-square inputs.

| Input resolution | Flash | nanoVLM-460M | LFM2.5-VL-450M | SmolVLM2-500M | Qwen3.5-0.8B |
| --- | --- | --- | --- | --- | --- |
| 512x512 | **64** | 1088 | 256 | 1088 | 256 |
| 512x1024 | **192** | 576 | 242 | 576 | 512 |
| 1024x662 | 320 | 832 | **228** | 832 | 672 |
| 2048x1024 | **576** | **576** | 2290 | **576** | 2048 |

*Table 5. Visual-token count at different input resolutions. Lower is better.*

### On-device time to first token

Flash achieves the lowest latency across all tested devices. On the common runtime, it reduces TTFT by **11.9–25.1x relative to nanoVLM-460M and SmolVLM2-500M**. Selecting the fastest available backend on each device, Flash is also **1.3–2.4x faster than LFM2.5-VL-450M** and **2.3–3.5x faster than Qwen3.5-0.8B**. This reduction follows the substantially shorter visual sequence. All device numbers are measured **on real phones** (Pixel 9, Galaxy S23, Galaxy S25 Ultra, iPhone 15) using **4-bit (Q4_0) GGUF** builds. TTFT is what a user feels when they point the camera and ask a question, and it is where Flash's token reduction pays off most.

![Figure 5. On-device time to first token across models](https://cdn-uploads.huggingface.co/production/uploads/6a512bc901d52eda49267fb8/ISzfflWxPXBbcP_nmcB28.png)

*Figure 5. On-device time to first token across models. TTFT is measured on four mobile devices using a 512 × 512 input. Each entry reports CPU/GPU latency in seconds. Lower is better.*

Memory follows the same pattern: at 512x512, Flash reduces peak resident memory by 24-39% on Android and 41-65% on iPhone 15 against the full-token baselines, and beats them on decode throughput in 13 of 16 device and backend configurations. LFM2.5-VL-450M achieves the lowest absolute memory and highest throughput in most settings, showing both are strongly affected by architecture and runtime as well as token count.

### On-device time to last token

Practical responsiveness also depends on the time to produce a complete response. Because standard VLMEvalKit queries demand few-token outputs, we profile with the prompt "Please describe the image in one sentence", which proxies a realistic interaction while constraining response length.

Flash achieves the lowest time-to-last-token across all tested Android devices, requiring 10.6s on the Pixel 9, 7.4s on the Galaxy S23, and 4.2s on the Galaxy S25 Ultra. Compared to LFM2.5-VL-450M, the most comparable baseline in terms of instruction following and response length, **this yields speedups of 2.5x, 2.1x, and 1.8x** respectively (on the iPhone 15, both models finish in 0.7s). Crucially, **Flash generates slightly more tokens on average than LFM2.5-VL-450M (35.9 vs 29.1)**, so the latency advantage is not an artifact of shorter responses. nanoVLM and SmolVLM2 average 136.4 and 254.4 tokens despite the explicit one-sentence constraint, so their higher TTLT reflects the computational penalty of poor instruction adherence.

![Figure 6. Time to Last Token on different mobile devices](https://cdn-uploads.huggingface.co/production/uploads/6a512bc901d52eda49267fb8/dsnx4jJ007swTdxLEokuL.png)

*Figure 6. Time to Last Token (TTLT, in seconds) on different mobile devices. Lower is better. Visual and output token counts are also reported for comparison.*

### What Flash costs

Flash preserves the core capabilities of the full model at a significantly reduced cost, scoring 61.4 normalized against 62.3, or about 99% of the quality. Gaps are under one point on AI2D, POPE, and MMMU, and the efficient variant even improves on MME (+78 points), MM-IFEval (+1.4), and InfoVQA (+1.3). More noticeable degradations emerge on OCR-heavy and fine-grained reasoning benchmarks, particularly TextVQA, OCRBench, and ScienceQA, suggesting that tasks reliant on high-resolution text recognition are inherently more sensitive to this optimization. If your workload is dense document OCR, use the full model; otherwise Flash is a highly favorable operating point.

---

## Usage

VisionPsy-Nano runs across three interchangeable runtimes, so you can move from a research prototype to a phone without changing checkpoints. The 🤗 Transformers reference path is shown below; for high-throughput **vLLM** [19] serving and on-device **llama.cpp** [18] (GGUF) deployment, the [inference repository](https://github.com/tether-ai-research/qvac-visionpsy-nano) ships ready-to-run setup, build, and inference scripts. Quantized GGUF builds are available for on-device use ([VisionPsy-Nano-460M-GGUFs](https://huggingface.co/qvac/VisionPsy-Nano-460M-GGUFs) and [VisionPsy-Nano-460M-Flash-GGUFs](https://huggingface.co/qvac/VisionPsy-Nano-460M-Flash-GGUFs)); the **5-bit (Q5_K_M)** build of Flash is a good quality/size operating point, and a **4-bit (Q4_0)** build is used for the on-device latency numbers above.

Both models load directly with 🤗 Transformers via `trust_remote_code`, no extra repo to clone. Requires Python ≥ 3.10, `transformers>=4.46`, and PyTorch ≥ 2.4 (CUDA GPU recommended; CPU works, slower).

```python
import torch
from PIL import Image
from transformers import AutoModelForImageTextToText, AutoProcessor

repo = "qvac/VisionPsy-Nano-460M"
device = "cuda" if torch.cuda.is_available() else "cpu"

model = AutoModelForImageTextToText.from_pretrained(
    repo,
    trust_remote_code=True,
    dtype="auto" if device == "cuda" else torch.float32,
).to(device).eval()
processor = AutoProcessor.from_pretrained(repo, trust_remote_code=True)

# apply_deploy_profile() enables torch.compile + CUDA graphs (fastest on GPU);
# use apply_eager_profile() for plain eager execution or CPU.
if device == "cuda":
    model.apply_deploy_profile(model.device)
else:
    model.apply_eager_profile()

# The processor applies the chat template and inserts image tokens for you —
# just pass the raw image(s) and a plain-text prompt.
image = Image.open("your_image.jpg").convert("RGB")
inputs = processor(images=image, text="What is in this image?", return_tensors="pt")
inputs = {
    k: (v.to(device) if torch.is_tensor(v) else v)
    for k, v in inputs.items()
    if v is not None
}
inputs.pop("pixel_values", None)

with torch.inference_mode():
    out = model.generate(**inputs, max_new_tokens=128, greedy=True)
print(processor.batch_decode(out, skip_special_tokens=True)[0].strip())
```

---

## Intended use & limitations

VisionPsy-Nano targets latency- and memory-constrained, on-device multimodal applications: visual question answering, document/chart/diagram understanding, scene-text reading, and lightweight visual instruction following. Because of its small size, we recommend fine-tuning on your specific domain to maximize quality.

- **Single-image by design:** recommend one image per query; multi-image prompts are outside its intended use.
- As a compact model it may occasionally hallucinate or miscount, and is best on focused tasks rather than very dense documents or long multi-step math.
- **Primarily English**; other languages are not officially supported yet.
- **Not** intended for safety-critical or high-stakes automated decisions.

---

## Conclusion

VisionPsy-Nano shows that a compact, single-image vision-language model can be **best-in-class at ~0.5B**, beat models up to ~2x larger on the skills that matter, and still run **fast enough and small enough to ship on a phone**. The two variants let builders choose their point on the quality/latency curve: **VisionPsy-Nano-460M** for maximum accuracy, **VisionPsy-Nano-460M-Flash** for maximum responsiveness. The central lesson is the same as its methodology: **failure-driven data, checkpoint merging, and alignment**, not raw scale, are what close the gap to much larger models at the edge.

## What's next

A full technical report covering the complete 17-benchmark results, the failure-analysis framework, per-stage data curation, the TIES merge configuration, and the full safety evaluation will follow this post. We are also working on an in-browser WebGPU demo so you can try both variants without installing anything, and we welcome fine-tunes, quantizations, and bug reports on the [GitHub repository](https://github.com/tether-ai-research/qvac-visionpsy-nano).

## Acknowledgements

Built on the excellent open-source work of [nanoVLM](https://github.com/huggingface/nanoVLM) [3], [SmolLM2](https://huggingface.co/HuggingFaceTB/SmolLM2-360M-Instruct) [10], and [SigLIP2](https://huggingface.co/google/siglip2-base-patch16-512) [9], and evaluated with [VLMEvalKit](https://github.com/open-compass/VLMEvalKit) [7].

## Citation

```bibtex
@misc{visionpsynano2026,
title = {VisionPsy-Nano: State-of-the-Art On-Device Vision-Language Models},
author = {Tether AI Research},
year = {2026},
note = {Hugging Face blog}
}
```

## References

[1] Liquid AI. "LFM2.5-VL-450M." Hugging Face model card, 2026. https://huggingface.co/LiquidAI/LFM2.5-VL-450M

[2] Hugging Face. "SmolVLM2-500M-Video-Instruct." Hugging Face model card, 2025. https://huggingface.co/HuggingFaceTB/SmolVLM2-500M-Video-Instruct. Related paper: Marafioti, A. et al. "SmolVLM: Redefining Small and Efficient Multimodal Models." arXiv preprint arXiv:2504.05299, 2025. https://arxiv.org/abs/2504.05299

[3] Hugging Face. "nanoVLM-460M-8k." Hugging Face model card, 2025. https://huggingface.co/lusxvr/nanoVLM-460M-8k. Project code: https://github.com/huggingface/nanoVLM

[4] Vasu, P. K. A. et al. "FastVLM: Efficient Vision Encoding for Vision Language Models." CVPR, 2025. https://arxiv.org/abs/2412.13303. Model card: https://huggingface.co/apple/FastVLM-0.5B

[5] Qwen Team. "Qwen3.5-0.8B." Hugging Face model card, 2026. https://huggingface.co/Qwen/Qwen3.5-0.8B

[6] Wang, W. et al. "InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency." arXiv preprint arXiv:2508.18265, 2025. https://arxiv.org/abs/2508.18265. Model card: https://huggingface.co/OpenGVLab/InternVL3_5-1B

[7] Duan, H. et al. "VLMEvalKit: An Open-Source Toolkit for Evaluating Large Multi-Modality Models." ACM Multimedia, pp. 11198–11201, 2024. https://arxiv.org/abs/2407.11691. Software: https://github.com/open-compass/VLMEvalKit

[8] Qwen Team. "Qwen3.6-27B." Hugging Face model card, 2026. https://huggingface.co/Qwen/Qwen3.6-27B

[9] Tschannen, M. et al. "SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features." arXiv preprint arXiv:2502.14786, 2025. https://arxiv.org/abs/2502.14786. Model card: https://huggingface.co/google/siglip2-base-patch16-512

[10] Ben Allal, L. et al. "SmolLM2: When Smol Goes Big — Data-Centric Training of a Small Language Model." arXiv preprint arXiv:2502.02737, 2025. https://arxiv.org/abs/2502.02737. Model card: https://huggingface.co/HuggingFaceTB/SmolLM2-360M-Instruct

[11] NVIDIA. "Nemotron-Image-Training-v3." Hugging Face dataset card, 2026. https://huggingface.co/datasets/nvidia/Nemotron-Image-Training-v3

[12] Wiedmann, L. et al. "FineVision: Open Data Is All You Need." arXiv preprint arXiv:2510.17269, 2025. https://arxiv.org/abs/2510.17269. Dataset card: https://huggingface.co/datasets/HuggingFaceM4/FineVision

[13] Sabbaghi, M., Pappas, G., Javanmard, A., and Hassani, H. "InfoSFT: Learn More and Forget Less with Information-Aware Token Weighting." arXiv preprint arXiv:2605.14967, 2026. https://arxiv.org/abs/2605.14967

[14] Yadav, P., Tam, D., Choshen, L., Raffel, C., and Bansal, M. "TIES-Merging: Resolving Interference When Merging Models." NeurIPS 36, 2023. https://arxiv.org/abs/2306.01708. Code: https://github.com/prateeky2806/ties-merging

[15] Wang, W. et al. "Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization." arXiv preprint arXiv:2411.10442, 2024. https://arxiv.org/abs/2411.10442

[16] Ji, J. et al. "Safe RLHF-V: Safe Reinforcement Learning from Multi-modal Human Feedback." arXiv preprint arXiv:2503.17682, 2025. https://arxiv.org/abs/2503.17682. Dataset card: https://huggingface.co/datasets/PKU-Alignment/PKU-SafeRLHF-V

[17] Gong, Y. et al. "FigStep: Jailbreaking Large Vision-Language Models via Typographic Visual Prompts." AAAI 39(22), pp. 23951–23959, 2025. https://doi.org/10.1609/aaai.v39i22.34568. Code: https://github.com/ThuCCSLab/FigStep

[18] Gerganov, G. et al. "llama.cpp: LLM Inference in C/C++." Software repository, 2023–2026. https://github.com/ggml-org/llama.cpp

[19] Kwon, W. et al. "Efficient Memory Management for Large Language Model Serving with PagedAttention." SOSP, 2023. https://arxiv.org/abs/2309.06180. Software: https://github.com/vllm-project/vllm



## Copyright Complaints

We will take appropriate actions in response to notice of copyright infringement. If you believe your work has been used or copied in a manner that infringes upon your intellectual property rights, please email data-apps@tether.io identifying and describing both the copyrighted work and the alleged infringing content to file a notice of infringement.



# Licensing Information

**Developed by:** Tether AI Research

**Model license:** [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0.txt)

This model, which was finetuned using the software described above, is
licensed by Tether Data, S.A. de C.V. under the
[Apache 2.0 license](https://www.apache.org/licenses/LICENSE-2.0.txt). As described above,
this model is a version of the
[nanoVLM-460M-8k](https://huggingface.co/lusxvr/nanoVLM-460M-8k) pre-trained model, which is made
available under the [MIT license](https://opensource.org/license/mit).

The [FineVision](https://huggingface.co/datasets/HuggingFaceM4/FineVision) dataset is made available
under the [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/legalcode.en) (Creative Commons —
Attribution 4.0) license. FineVision is an aggregation of a number of public sources unified into a
single corpus. Individual subsets within the collection may inherit specific underlying terms from
their original creators. As described above, a subset of the FineVision dataset was used
as a part of finetuning the model.

The [NVIDIA Nemotron-Image-Training-v3](https://huggingface.co/datasets/nvidia/Nemotron-Image-Training-v3)
dataset is made available under the
[CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/legalcode.en) (Creative Commons —
Attribution 4.0). The [mPLUG TinyChartData](https://huggingface.co/datasets/mPLUG/TinyChartData)
dataset is made available under the [Apache 2.0 license](https://www.apache.org/licenses/LICENSE-2.0.txt).
The [TabMWP](https://promptpg.github.io/) dataset is made available under the
[CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.en) (Creative Commons —
Attribution-NonCommercial-ShareAlike 4.0). The [PopVQA](https://huggingface.co/datasets/idoco/PopVQA)
dataset is made available under the [MIT license](https://opensource.org/license/mit). The
[InfoSeek](https://github.com/open-vision-language/infoseek) dataset is made available under the
[Apache 2.0 license](https://www.apache.org/licenses/LICENSE-2.0.txt). The
[MMKU-Bench](https://huggingface.co/datasets/baochenfu/MMKU-Bench) dataset is made available under
the [Apache 2.0 license](https://www.apache.org/licenses/LICENSE-2.0.txt). The
[VisionFoundry-10K](https://huggingface.co/datasets/zlab-princeton/VisionFoundry-10K) dataset is
made available under the [Apache 2.0 license](https://www.apache.org/licenses/LICENSE-2.0.txt). The
[PKU-SafeRLHF-V](https://huggingface.co/datasets/PKU-Alignment/PKU-SafeRLHF-V) dataset is made
available under the [CC-BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/legalcode.en)
(Attribution-NonCommercial 4.0 International). As described above,
the NVIDIA Nemotron-Image-Training-v3, mPLUG TinyChartData, TabMWP, PopVQA, InfoSeek,
MMKU-Bench, VisionFoundry-10K and PKU-SafeRLHF-V datasets were used as a part of finetuning the
model.

Licenses are reproduced below.

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```

## MIT License

```text
MIT License

Copyright (c) 2025 Luis Wiedmann and Aritra Roy Gosthipaty and Andrés Marafioti

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     a.	Unless otherwise separately undertaken by the Licensor, to the extent possible, the Licensor offers the Licensed Material as-is and as-available, and makes no representations or warranties of any kind concerning the Licensed Material, whether express, implied, statutory, or other. This includes, without limitation, warranties of title, merchantability, fitness for a particular purpose, non-infringement, absence of latent or other defects, accuracy, or the presence or absence of errors, whether or not known or discoverable. Where disclaimers of warranties are not allowed in full or in part, this disclaimer may not apply to You.

     b.	To the extent possible, in no event will the Licensor be liable to You on any legal theory (including, without limitation, negligence) or otherwise for any direct, special, indirect, incidental, consequential, punitive, exemplary, or other losses, costs, expenses, or damages arising out of this Public License or use of the Licensed Material, even if the Licensor has been advised of the possibility of such losses, costs, expenses, or damages. Where a limitation of liability is not allowed in full or in part, this limitation may not apply to You.

     c.	The disclaimer of warranties and limitation of liability provided above shall be interpreted in a manner that, to the extent possible, most closely approximates an absolute disclaimer and waiver of all liability.

Section 6 – Term and Termination.

     a.	This Public License applies for the term of the Copyright and Similar Rights licensed here. However, if You fail to comply with this Public License, then Your rights under this Public License terminate automatically.

     b.	Where Your right to use the Licensed Material has terminated under Section 6(a), it reinstates:

          1. automatically as of the date the violation is cured, provided it is cured within 30 days of Your discovery of the violation; or

          2. upon express reinstatement by the Licensor.

     c.	For the avoidance of doubt, this Section 6(b) does not affect any right the Licensor may have to seek remedies for Your violations of this Public License.

     d.	For the avoidance of doubt, the Licensor may also offer the Licensed Material under separate terms or conditions or stop distributing the Licensed Material at any time; however, doing so will not terminate this Public License.

     e.	Sections 1, 5, 6, 7, and 8 survive termination of this Public License.

Section 7 – Other Terms and Conditions.

     a.	The Licensor shall not be bound by any additional or different terms or conditions communicated by You unless expressly agreed.

     b.	Any arrangements, understandings, or agreements regarding the Licensed Material not stated herein are separate from and independent of the terms and conditions of this Public License.

Section 8 – Interpretation.

     a.	For the avoidance of doubt, this Public License does not, and shall not be interpreted to, reduce, limit, restrict, or impose conditions on any use of the Licensed Material that could lawfully be made without permission under this Public License.

     b.	To the extent possible, if any provision of this Public License is deemed unenforceable, it shall be automatically reformed to the minimum extent necessary to make it enforceable. If the provision cannot be reformed, it shall be severed from this Public License without affecting the enforceability of the remaining terms and conditions.

     c.	No term or condition of this Public License will be waived and no failure to comply consented to unless expressly agreed to by the Licensor.

     d.	Nothing in this Public License constitutes or may be interpreted as a limitation upon, or waiver of, any privileges and immunities that apply to the Licensor or You, including from the legal processes of any jurisdiction or authority.

Creative Commons is not a party to its public licenses. Notwithstanding, Creative Commons may elect to apply one of its public licenses to material it publishes and in those instances will be considered the “Licensor.” Except for the limited purpose of indicating that material is shared under a Creative Commons public license or as otherwise permitted by the Creative Commons policies published at creativecommons.org/policies, Creative Commons does not authorize the use of the trademark “Creative Commons” or any other trademark or logo of Creative Commons without its prior written consent including, without limitation, in connection with any unauthorized modifications to any of its public licenses or any other arrangements, understandings, or agreements concerning use of licensed material. For the avoidance of doubt, this paragraph does not form part of the public licenses.

Creative Commons may be contacted at creativecommons.org.
```

## CC BY-NC 4.0

```text
Creative Commons Attribution-NonCommercial 4.0 International

 Creative Commons Corporation (“Creative Commons”) is not a law firm and does not provide legal services or legal advice. Distribution of Creative Commons public licenses does not create a lawyer-client or other relationship. Creative Commons makes its licenses and related information available on an “as-is” basis. Creative Commons gives no warranties regarding its licenses, any material licensed under their terms and conditions, or any related information. Creative Commons disclaims all liability for damages resulting from their use to the fullest extent possible.

Using Creative Commons Public Licenses

Creative Commons public licenses provide a standard set of terms and conditions that creators and other rights holders may use to share original works of authorship and other material subject to copyright and certain other rights specified in the public license below. The following considerations are for informational purposes only, are not exhaustive, and do not form part of our licenses.

Considerations for licensors: Our public licenses are intended for use by those authorized to give the public permission to use material in ways otherwise restricted by copyright and certain other rights. Our licenses are irrevocable. Licensors should read and understand the terms and conditions of the license they choose before applying it. Licensors should also secure all rights necessary before applying our licenses so that the public can reuse the material as expected. Licensors should clearly mark any material not subject to the license. This includes other CC-licensed material, or material used under an exception or limitation to copyright. More considerations for licensors.

Considerations for the public: By using one of our public licenses, a licensor grants the public permission to use the licensed material under specified terms and conditions. If the licensor’s permission is not necessary for any reason–for example, because of any applicable exception or limitation to copyright–then that use is not regulated by the license. Our licenses grant only permissions under copyright and certain other rights that a licensor has authority to grant. Use of the licensed material may still be restricted for other reasons, including because others have copyright or other rights in the material. A licensor may make special requests, such as asking that all changes be marked or described. Although not required by our licenses, you are encouraged to respect those requests where reasonable. More considerations for the public.

Creative Commons Attribution-NonCommercial 4.0 International Public License

By exercising the Licensed Rights (defined below), You accept and agree to be bound by the terms and conditions of this Creative Commons Attribution-NonCommercial 4.0 International Public License ("Public License"). To the extent this Public License may be interpreted as a contract, You are granted the Licensed Rights in consideration of Your acceptance of these terms and conditions, and the Licensor grants You such rights in consideration of benefits the Licensor receives from making the Licensed Material available under these terms and conditions.

Section 1 – Definitions.

     a.	Adapted Material means material subject to Copyright and Similar Rights that is derived from or based upon the Licensed Material and in which the Licensed Material is translated, altered, arranged, transformed, or otherwise modified in a manner requiring permission under the Copyright and Similar Rights held by the Licensor. For purposes of this Public License, where the Licensed Material is a musical work, performance, or sound recording, Adapted Material is always produced where the Licensed Material is synched in timed relation with a moving image.

     b.	Adapter's License means the license You apply to Your Copyright and Similar Rights in Your contributions to Adapted Material in accordance with the terms and conditions of this Public License.

     c.	Copyright and Similar Rights means copyright and/or similar rights closely related to copyright including, without limitation, performance, broadcast, sound recording, and Sui Generis Database Rights, without regard to how the rights are labeled or categorized. For purposes of this Public License, the rights specified in Section 2(b)(1)-(2) are not Copyright and Similar Rights.

     d.	Effective Technological Measures means those measures that, in the absence of proper authority, may not be circumvented under laws fulfilling obligations under Article 11 of the WIPO Copyright Treaty adopted on December 20, 1996, and/or similar international agreements.

     e.	Exceptions and Limitations means fair use, fair dealing, and/or any other exception or limitation to Copyright and Similar Rights that applies to Your use of the Licensed Material.

     f.	Licensed Material means the artistic or literary work, database, or other material to which the Licensor applied this Public License.

     g.	Licensed Rights means the rights granted to You subject to the terms and conditions of this Public License, which are limited to all Copyright and Similar Rights that apply to Your use of the Licensed Material and that the Licensor has authority to license.

     h.	Licensor means the individual(s) or entity(ies) granting rights under this Public License.

     i.	NonCommercial means not primarily intended for or directed towards commercial advantage or monetary compensation. For purposes of this Public License, the exchange of the Licensed Material for other material subject to Copyright and Similar Rights by digital file-sharing or similar means is NonCommercial provided there is no payment of monetary compensation in connection with the exchange.

     j.	Share means to provide material to the public by any means or process that requires permission under the Licensed Rights, such as reproduction, public display, public performance, distribution, dissemination, communication, or importation, and to make material available to the public including in ways that members of the public may access the material from a place and at a time individually chosen by them.

     k.	Sui Generis Database Rights means rights other than copyright resulting from Directive 96/9/EC of the European Parliament and of the Council of 11 March 1996 on the legal protection of databases, as amended and/or succeeded, as well as other essentially equivalent rights anywhere in the world.

     l.	You means the individual or entity exercising the Licensed Rights under this Public License. Your has a corresponding meaning.

Section 2 – Scope.

     a.	License grant.

          1. Subject to the terms and conditions of this Public License, the Licensor hereby grants You a worldwide, royalty-free, non-sublicensable, non-exclusive, irrevocable license to exercise the Licensed Rights in the Licensed Material to:

               A. reproduce and Share the Licensed Material, in whole or in part, for NonCommercial purposes only; and

               B. produce, reproduce, and Share Adapted Material for NonCommercial purposes only.

          2. Exceptions and Limitations. For the avoidance of doubt, where Exceptions and Limitations apply to Your use, this Public License does not apply, and You do not need to comply with its terms and conditions.

          3. Term. The term of this Public License is specified in Section 6(a).

          4. Media and formats; technical modifications allowed. The Licensor authorizes You to exercise the Licensed Rights in all media and formats whether now known or hereafter created, and to make technical modifications necessary to do so. The Licensor waives and/or agrees not to assert any right or authority to forbid You from making technical modifications necessary to exercise the Licensed Rights, including technical modifications necessary to circumvent Effective Technological Measures. For purposes of this Public License, simply making modifications authorized by this Section 2(a)(4) never produces Adapted Material.

          5. Downstream recipients.

               A. Offer from the Licensor – Licensed Material. Every recipient of the Licensed Material automatically receives an offer from the Licensor to exercise the Licensed Rights under the terms and conditions of this Public License.

               B. No downstream restrictions. You may not offer or impose any additional or different terms or conditions on, or apply any Effective Technological Measures to, the Licensed Material if doing so restricts exercise of the Licensed Rights by any recipient of the Licensed Material.

          6. No endorsement. Nothing in this Public License constitutes or may be construed as permission to assert or imply that You are, or that Your use of the Licensed Material is, connected with, or sponsored, endorsed, or granted official status by, the Licensor or others designated to receive attribution as provided in Section 3(a)(1)(A)(i).

     b.	Other rights.

          1. Moral rights, such as the right of integrity, are not licensed under this Public License, nor are publicity, privacy, and/or other similar personality rights; however, to the extent possible, the Licensor waives and/or agrees not to assert any such rights held by the Licensor to the limited extent necessary to allow You to exercise the Licensed Rights, but not otherwise.

          2. Patent and trademark rights are not licensed under this Public License.

          3. To the extent possible, the Licensor waives any right to collect royalties from You for the exercise of the Licensed Rights, whether directly or through a collecting society under any voluntary or waivable statutory or compulsory licensing scheme. In all other cases the Licensor expressly reserves any right to collect such royalties, including when the Licensed Material is used other than for NonCommercial purposes.

Section 3 – License Conditions.

Your exercise of the Licensed Rights is expressly made subject to the following conditions.

     a.	Attribution.

          1. If You Share the Licensed Material (including in modified form), You must:

               A. retain the following if it is supplied by the Licensor with the Licensed Material:

                    i.	identification of the creator(s) of the Licensed Material and any others designated to receive attribution, in any reasonable manner requested by the Licensor (including by pseudonym if designated);

                    ii.	a copyright notice;

                    iii. a notice that refers to this Public License;

                    iv.	a notice that refers to the disclaimer of warranties;

                    v.	a URI or hyperlink to the Licensed Material to the extent reasonably practicable;

               B. indicate if You modified the Licensed Material and retain an indication of any previous modifications; and

               C. indicate the Licensed Material is licensed under this Public License, and include the text of, or the URI or hyperlink to, this Public License.

          2. You may satisfy the conditions in Section 3(a)(1) in any reasonable manner based on the medium, means, and context in which You Share the Licensed Material. For example, it may be reasonable to satisfy the conditions by providing a URI or hyperlink to a resource that includes the required information.

          3. If requested by the Licensor, You must remove any of the information required by Section 3(a)(1)(A) to the extent reasonably practicable.

          4. If You Share Adapted Material You produce, the Adapter's License You apply must not prevent recipients of the Adapted Material from complying with this Public License.

Section 4 – Sui Generis Database Rights.

Where the Licensed Rights include Sui Generis Database Rights that apply to Your use of the Licensed Material:

     a.	for the avoidance of doubt, Section 2(a)(1) grants You the right to extract, reuse, reproduce, and Share all or a substantial portion of the contents of the database for NonCommercial purposes only;

     b.	if You include all or a substantial portion of the database contents in a database in which You have Sui Generis Database Rights, then the database in which You have Sui Generis Database Rights (but not its individual contents) is Adapted Material; and

     c.	You must comply with the conditions in Section 3(a) if You Share all or a substantial portion of the contents of the database.
For the avoidance of doubt, this Section 4 supplements and does not replace Your obligations under this Public License where the Licensed Rights include other Copyright and Similar Rights.

Section 5 – Disclaimer of Warranties and Limitation of Liability.

     a.	Unless otherwise separately undertaken by the Licensor, to the extent possible, the Licensor offers the Licensed Material as-is and as-available, and makes no representations or warranties of any kind concerning the Licensed Material, whether express, implied, statutory, or other. This includes, without limitation, warranties of title, merchantability, fitness for a particular purpose, non-infringement, absence of latent or other defects, accuracy, or the presence or absence of errors, whether or not known or discoverable. Where disclaimers of warranties are not allowed in full or in part, this disclaimer may not apply to You.

     b.	To the extent possible, in no event will the Licensor be liable to You on any legal theory (including, without limitation, negligence) or otherwise for any direct, special, indirect, incidental, consequential, punitive, exemplary, or other losses, costs, expenses, or damages arising out of this Public License or use of the Licensed Material, even if the Licensor has been advised of the possibility of such losses, costs, expenses, or damages. Where a limitation of liability is not allowed in full or in part, this limitation may not apply to You.

     c.	The disclaimer of warranties and limitation of liability provided above shall be interpreted in a manner that, to the extent possible, most closely approximates an absolute disclaimer and waiver of all liability.

Section 6 – Term and Termination.

     a.	This Public License applies for the term of the Copyright and Similar Rights licensed here. However, if You fail to comply with this Public License, then Your rights under this Public License terminate automatically.

     b.	Where Your right to use the Licensed Material has terminated under Section 6(a), it reinstates:

          1. automatically as of the date the violation is cured, provided it is cured within 30 days of Your discovery of the violation; or

          2. upon express reinstatement by the Licensor.

     For the avoidance of doubt, this Section 6(b) does not affect any right the Licensor may have to seek remedies for Your violations of this Public License.

     c.	For the avoidance of doubt, the Licensor may also offer the Licensed Material under separate terms or conditions or stop distributing the Licensed Material at any time; however, doing so will not terminate this Public License.

     d.	Sections 1, 5, 6, 7, and 8 survive termination of this Public License.

Section 7 – Other Terms and Conditions.

     a.	The Licensor shall not be bound by any additional or different terms or conditions communicated by You unless expressly agreed.

     b.	Any arrangements, understandings, or agreements regarding the Licensed Material not stated herein are separate from and independent of the terms and conditions of this Public License.

Section 8 – Interpretation.

     a.	For the avoidance of doubt, this Public License does not, and shall not be interpreted to, reduce, limit, restrict, or impose conditions on any use of the Licensed Material that could lawfully be made without permission under this Public License.

     b.	To the extent possible, if any provision of this Public License is deemed unenforceable, it shall be automatically reformed to the minimum extent necessary to make it enforceable. If the provision cannot be reformed, it shall be severed from this Public License without affecting the enforceability of the remaining terms and conditions.

     c.	No term or condition of this Public License will be waived and no failure to comply consented to unless expressly agreed to by the Licensor.

     d.	Nothing in this Public License constitutes or may be interpreted as a limitation upon, or waiver of, any privileges and immunities that apply to the Licensor or You, including from the legal processes of any jurisdiction or authority.

Creative Commons is not a party to its public licenses. Notwithstanding, Creative Commons may elect to apply one of its public licenses to material it publishes and in those instances will be considered the “Licensor.” Except for the limited purpose of indicating that material is shared under a Creative Commons public license or as otherwise permitted by the Creative Commons policies published at creativecommons.org/policies, Creative Commons does not authorize the use of the trademark “Creative Commons” or any other trademark or logo of Creative Commons without its prior written consent including, without limitation, in connection with any unauthorized modifications to any of its public licenses or any other arrangements, understandings, or agreements concerning use of licensed material. For the avoidance of doubt, this paragraph does not form part of the public licenses.

Creative Commons may be contacted at creativecommons.org.
```

## CC BY-NC-SA 4.0

```text
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International

 Creative Commons Corporation (“Creative Commons”) is not a law firm and does not provide legal services or legal advice. Distribution of Creative Commons public licenses does not create a lawyer-client or other relationship. Creative Commons makes its licenses and related information available on an “as-is” basis. Creative Commons gives no warranties regarding its licenses, any material licensed under their terms and conditions, or any related information. Creative Commons disclaims all liability for damages resulting from their use to the fullest extent possible.

Using Creative Commons Public Licenses

Creative Commons public licenses provide a standard set of terms and conditions that creators and other rights holders may use to share original works of authorship and other material subject to copyright and certain other rights specified in the public license below. The following considerations are for informational purposes only, are not exhaustive, and do not form part of our licenses.

Considerations for licensors: Our public licenses are intended for use by those authorized to give the public permission to use material in ways otherwise restricted by copyright and certain other rights. Our licenses are irrevocable. Licensors should read and understand the terms and conditions of the license they choose before applying it. Licensors should also secure all rights necessary before applying our licenses so that the public can reuse the material as expected. Licensors should clearly mark any material not subject to the license. This includes other CC-licensed material, or material used under an exception or limitation to copyright. More considerations for licensors.

Considerations for the public: By using one of our public licenses, a licensor grants the public permission to use the licensed material under specified terms and conditions. If the licensor’s permission is not necessary for any reason–for example, because of any applicable exception or limitation to copyright–then that use is not regulated by the license. Our licenses grant only permissions under copyright and certain other rights that a licensor has authority to grant. Use of the licensed material may still be restricted for other reasons, including because others have copyright or other rights in the material. A licensor may make special requests, such as asking that all changes be marked or described. Although not required by our licenses, you are encouraged to respect those requests where reasonable. More considerations for the public.

Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public License

By exercising the Licensed Rights (defined below), You accept and agree to be bound by the terms and conditions of this Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public License ("Public License"). To the extent this Public License may be interpreted as a contract, You are granted the Licensed Rights in consideration of Your acceptance of these terms and conditions, and the Licensor grants You such rights in consideration of benefits the Licensor receives from making the Licensed Material available under these terms and conditions.

Section 1 – Definitions.

     a.	Adapted Material means material subject to Copyright and Similar Rights that is derived from or based upon the Licensed Material and in which the Licensed Material is translated, altered, arranged, transformed, or otherwise modified in a manner requiring permission under the Copyright and Similar Rights held by the Licensor. For purposes of this Public License, where the Licensed Material is a musical work, performance, or sound recording, Adapted Material is always produced where the Licensed Material is synched in timed relation with a moving image.

     b.	Adapter's License means the license You apply to Your Copyright and Similar Rights in Your contributions to Adapted Material in accordance with the terms and conditions of this Public License.

     c.	BY-NC-SA Compatible License means a license listed at creativecommons.org/compatiblelicenses, approved by Creative Commons as essentially the equivalent of this Public License.

     d.	Copyright and Similar Rights means copyright and/or similar rights closely related to copyright including, without limitation, performance, broadcast, sound recording, and Sui Generis Database Rights, without regard to how the rights are labeled or categorized. For purposes of this Public License, the rights specified in Section 2(b)(1)-(2) are not Copyright and Similar Rights.

     e.	Effective Technological Measures means those measures that, in the absence of proper authority, may not be circumvented under laws fulfilling obligations under Article 11 of the WIPO Copyright Treaty adopted on December 20, 1996, and/or similar international agreements.

     f.	Exceptions and Limitations means fair use, fair dealing, and/or any other exception or limitation to Copyright and Similar Rights that applies to Your use of the Licensed Material.

     g.	License Elements means the license attributes listed in the name of a Creative Commons Public License. The License Elements of this Public License are Attribution, NonCommercial, and ShareAlike.

     h.	Licensed Material means the artistic or literary work, database, or other material to which the Licensor applied this Public License.

     i.	Licensed Rights means the rights granted to You subject to the terms and conditions of this Public License, which are limited to all Copyright and Similar Rights that apply to Your use of the Licensed Material and that the Licensor has authority to license.

     j.	Licensor means the individual(s) or entity(ies) granting rights under this Public License.

     k.	NonCommercial means not primarily intended for or directed towards commercial advantage or monetary compensation. For purposes of this Public License, the exchange of the Licensed Material for other material subject to Copyright and Similar Rights by digital file-sharing or similar means is NonCommercial provided there is no payment of monetary compensation in connection with the exchange.

     l.	Share means to provide material to the public by any means or process that requires permission under the Licensed Rights, such as reproduction, public display, public performance, distribution, dissemination, communication, or importation, and to make material available to the public including in ways that members of the public may access the material from a place and at a time individually chosen by them.

     m.	Sui Generis Database Rights means rights other than copyright resulting from Directive 96/9/EC of the European Parliament and of the Council of 11 March 1996 on the legal protection of databases, as amended and/or succeeded, as well as other essentially equivalent rights anywhere in the world.

     n.	You means the individual or entity exercising the Licensed Rights under this Public License. Your has a corresponding meaning.

Section 2 – Scope.

     a.	License grant.

          1. Subject to the terms and conditions of this Public License, the Licensor hereby grants You a worldwide, royalty-free, non-sublicensable, non-exclusive, irrevocable license to exercise the Licensed Rights in the Licensed Material to:

               A. reproduce and Share the Licensed Material, in whole or in part, for NonCommercial purposes only; and

               B. produce, reproduce, and Share Adapted Material for NonCommercial purposes only.

          2. Exceptions and Limitations. For the avoidance of doubt, where Exceptions and Limitations apply to Your use, this Public License does not apply, and You do not need to comply with its terms and conditions.

          3. Term. The term of this Public License is specified in Section 6(a).

          4. Media and formats; technical modifications allowed. The Licensor authorizes You to exercise the Licensed Rights in all media and formats whether now known or hereafter created, and to make technical modifications necessary to do so. The Licensor waives and/or agrees not to assert any right or authority to forbid You from making technical modifications necessary to exercise the Licensed Rights, including technical modifications necessary to circumvent Effective Technological Measures. For purposes of this Public License, simply making modifications authorized by this Section 2(a)(4) never produces Adapted Material.

          5. Downstream recipients.

               A. Offer from the Licensor – Licensed Material. Every recipient of the Licensed Material automatically receives an offer from the Licensor to exercise the Licensed Rights under the terms and conditions of this Public License.

               B. Additional offer from the Licensor – Adapted Material. Every recipient of Adapted Material from You automatically receives an offer from the Licensor to exercise the Licensed Rights in the Adapted Material under the conditions of the Adapter’s License You apply.

               C. No downstream restrictions. You may not offer or impose any additional or different terms or conditions on, or apply any Effective Technological Measures to, the Licensed Material if doing so restricts exercise of the Licensed Rights by any recipient of the Licensed Material.

          6. No endorsement. Nothing in this Public License constitutes or may be construed as permission to assert or imply that You are, or that Your use of the Licensed Material is, connected with, or sponsored, endorsed, or granted official status by, the Licensor or others designated to receive attribution as provided in Section 3(a)(1)(A)(i).

     b.	Other rights.

          1. Moral rights, such as the right of integrity, are not licensed under this Public License, nor are publicity, privacy, and/or other similar personality rights; however, to the extent possible, the Licensor waives and/or agrees not to assert any such rights held by the Licensor to the limited extent necessary to allow You to exercise the Licensed Rights, but not otherwise.

          2. Patent and trademark rights are not licensed under this Public License.

          3. To the extent possible, the Licensor waives any right to collect royalties from You for the exercise of the Licensed Rights, whether directly or through a collecting society under any voluntary or waivable statutory or compulsory licensing scheme. In all other cases the Licensor expressly reserves any right to collect such royalties, including when the Licensed Material is used other than for NonCommercial purposes.

Section 3 – License Conditions.

Your exercise of the Licensed Rights is expressly made subject to the following conditions.

     a.	Attribution.

          1. If You Share the Licensed Material (including in modified form), You must:

               A. retain the following if it is supplied by the Licensor with the Licensed Material:

                    i.	identification of the creator(s) of the Licensed Material and any others designated to receive attribution, in any reasonable manner requested by the Licensor (including by pseudonym if designated);

                    ii.	a copyright notice;

                    iii. a notice that refers to this Public License;

                    iv.	a notice that refers to the disclaimer of warranties;

                    v.	a URI or hyperlink to the Licensed Material to the extent reasonably practicable;

               B. indicate if You modified the Licensed Material and retain an indication of any previous modifications; and

               C. indicate the Licensed Material is licensed under this Public License, and include the text of, or the URI or hyperlink to, this Public License.

          2. You may satisfy the conditions in Section 3(a)(1) in any reasonable manner based on the medium, means, and context in which You Share the Licensed Material. For example, it may be reasonable to satisfy the conditions by providing a URI or hyperlink to a resource that includes the required information.

          3. If requested by the Licensor, You must remove any of the information required by Section 3(a)(1)(A) to the extent reasonably practicable.

     b.	ShareAlike.In addition to the conditions in Section 3(a), if You Share Adapted Material You produce, the following conditions also apply.

          1. The Adapter’s License You apply must be a Creative Commons license with the same License Elements, this version or later, or a BY-NC-SA Compatible License.

          2. You must include the text of, or the URI or hyperlink to, the Adapter's License You apply. You may satisfy this condition in any reasonable manner based on the medium, means, and context in which You Share Adapted Material.

          3. You may not offer or impose any additional or different terms or conditions on, or apply any Effective Technological Measures to, Adapted Material that restrict exercise of the rights granted under the Adapter's License You apply.

Section 4 – Sui Generis Database Rights.

Where the Licensed Rights include Sui Generis Database Rights that apply to Your use of the Licensed Material:

     a.	for the avoidance of doubt, Section 2(a)(1) grants You the right to extract, reuse, reproduce, and Share all or a substantial portion of the contents of the database for NonCommercial purposes only;

     b.	if You include all or a substantial portion of the database contents in a database in which You have Sui Generis Database Rights, then the database in which You have Sui Generis Database Rights (but not its individual contents) is Adapted Material, including for purposes of Section 3(b); and

     c.	You must comply with the conditions in Section 3(a) if You Share all or a substantial portion of the contents of the database.
For the avoidance of doubt, this Section 4 supplements and does not replace Your obligations under this Public License where the Licensed Rights include other Copyright and Similar Rights.

Section 5 – Disclaimer of Warranties and Limitation of Liability.

     a.	Unless otherwise separately undertaken by the Licensor, to the extent possible, the Licensor offers the Licensed Material as-is and as-available, and makes no representations or warranties of any kind concerning the Licensed Material, whether express, implied, statutory, or other. This includes, without limitation, warranties of title, merchantability, fitness for a particular purpose, non-infringement, absence of latent or other defects, accuracy, or the presence or absence of errors, whether or not known or discoverable. Where disclaimers of warranties are not allowed in full or in part, this disclaimer may not apply to You.

     b.	To the extent possible, in no event will the Licensor be liable to You on any legal theory (including, without limitation, negligence) or otherwise for any direct, special, indirect, incidental, consequential, punitive, exemplary, or other losses, costs, expenses, or damages arising out of this Public License or use of the Licensed Material, even if the Licensor has been advised of the possibility of such losses, costs, expenses, or damages. Where a limitation of liability is not allowed in full or in part, this limitation may not apply to You.

     c.	The disclaimer of warranties and limitation of liability provided above shall be interpreted in a manner that, to the extent possible, most closely approximates an absolute disclaimer and waiver of all liability.

Section 6 – Term and Termination.

     a.	This Public License applies for the term of the Copyright and Similar Rights licensed here. However, if You fail to comply with this Public License, then Your rights under this Public License terminate automatically.

     b.	Where Your right to use the Licensed Material has terminated under Section 6(a), it reinstates:

          1.	automatically as of the date the violation is cured, provided it is cured within 30 days of Your discovery of the violation; or

          2.	upon express reinstatement by the Licensor.

     For the avoidance of doubt, this Section 6(b) does not affect any right the Licensor may have to seek remedies for Your violations of this Public License.

     c.	For the avoidance of doubt, the Licensor may also offer the Licensed Material under separate terms or conditions or stop distributing the Licensed Material at any time; however, doing so will not terminate this Public License.

     d.	Sections 1, 5, 6, 7, and 8 survive termination of this Public License.

Section 7 – Other Terms and Conditions.

     a.	The Licensor shall not be bound by any additional or different terms or conditions communicated by You unless expressly agreed.

     b.	Any arrangements, understandings, or agreements regarding the Licensed Material not stated herein are separate from and independent of the terms and conditions of this Public License.

Section 8 – Interpretation.

     a.	For the avoidance of doubt, this Public License does not, and shall not be interpreted to, reduce, limit, restrict, or impose conditions on any use of the Licensed Material that could lawfully be made without permission under this Public License.

     b.	To the extent possible, if any provision of this Public License is deemed unenforceable, it shall be automatically reformed to the minimum extent necessary to make it enforceable. If the provision cannot be reformed, it shall be severed from this Public License without affecting the enforceability of the remaining terms and conditions.

     c.	No term or condition of this Public License will be waived and no failure to comply consented to unless expressly agreed to by the Licensor.

     d.	Nothing in this Public License constitutes or may be interpreted as a limitation upon, or waiver of, any privileges and immunities that apply to the Licensor or You, including from the legal processes of any jurisdiction or authority.

Creative Commons is not a party to its public licenses. Notwithstanding, Creative Commons may elect to apply one of its public licenses to material it publishes and in those instances will be considered the “Licensor.” Except for the limited purpose of indicating that material is shared under a Creative Commons public license or as otherwise permitted by the Creative Commons policies published at creativecommons.org/policies, Creative Commons does not authorize the use of the trademark “Creative Commons” or any other trademark or logo of Creative Commons without its prior written consent including, without limitation, in connection with any unauthorized modifications to any of its public licenses or any other arrangements, understandings, or agreements concerning use of licensed material. For the avoidance of doubt, this paragraph does not form part of the public licenses.

Creative Commons may be contacted at creativecommons.org.
```

## MIT License

```text
MIT License

Copyright (c) 2024 Ido Cohen, Daniela Gottesman, Mor Geva, Raja Giryes

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
```

## CC-BY-NC 4.0

```text
Creative Commons Attribution-NonCommercial 4.0 International

 Creative Commons Corporation (“Creative Commons”) is not a law firm and does not provide legal services or legal advice. Distribution of Creative Commons public licenses does not create a lawyer-client or other relationship. Creative Commons makes its licenses and related information available on an “as-is” basis. Creative Commons gives no warranties regarding its licenses, any material licensed under their terms and conditions, or any related information. Creative Commons disclaims all liability for damages resulting from their use to the fullest extent possible.

Using Creative Commons Public Licenses

Creative Commons public licenses provide a standard set of terms and conditions that creators and other rights holders may use to share original works of authorship and other material subject to copyright and certain other rights specified in the public license below. The following considerations are for informational purposes only, are not exhaustive, and do not form part of our licenses.

Considerations for licensors: Our public licenses are intended for use by those authorized to give the public permission to use material in ways otherwise restricted by copyright and certain other rights. Our licenses are irrevocable. Licensors should read and understand the terms and conditions of the license they choose before applying it. Licensors should also secure all rights necessary before applying our licenses so that the public can reuse the material as expected. Licensors should clearly mark any material not subject to the license. This includes other CC-licensed material, or material used under an exception or limitation to copyright. More considerations for licensors.

Considerations for the public: By using one of our public licenses, a licensor grants the public permission to use the licensed material under specified terms and conditions. If the licensor’s permission is not necessary for any reason–for example, because of any applicable exception or limitation to copyright–then that use is not regulated by the license. Our licenses grant only permissions under copyright and certain other rights that a licensor has authority to grant. Use of the licensed material may still be restricted for other reasons, including because others have copyright or other rights in the material. A licensor may make special requests, such as asking that all changes be marked or described. Although not required by our licenses, you are encouraged to respect those requests where reasonable. More considerations for the public.

Creative Commons Attribution-NonCommercial 4.0 International Public License

By exercising the Licensed Rights (defined below), You accept and agree to be bound by the terms and conditions of this Creative Commons Attribution-NonCommercial 4.0 International Public License ("Public License"). To the extent this Public License may be interpreted as a contract, You are granted the Licensed Rights in consideration of Your acceptance of these terms and conditions, and the Licensor grants You such rights in consideration of benefits the Licensor receives from making the Licensed Material available under these terms and conditions.

Section 1 – Definitions.

     a.	Adapted Material means material subject to Copyright and Similar Rights that is derived from or based upon the Licensed Material and in which the Licensed Material is translated, altered, arranged, transformed, or otherwise modified in a manner requiring permission under the Copyright and Similar Rights held by the Licensor. For purposes of this Public License, where the Licensed Material is a musical work, performance, or sound recording, Adapted Material is always produced where the Licensed Material is synched in timed relation with a moving image.

     b.	Adapter's License means the license You apply to Your Copyright and Similar Rights in Your contributions to Adapted Material in accordance with the terms and conditions of this Public License.

     c.	Copyright and Similar Rights means copyright and/or similar rights closely related to copyright including, without limitation, performance, broadcast, sound recording, and Sui Generis Database Rights, without regard to how the rights are labeled or categorized. For purposes of this Public License, the rights specified in Section 2(b)(1)-(2) are not Copyright and Similar Rights.

     d.	Effective Technological Measures means those measures that, in the absence of proper authority, may not be circumvented under laws fulfilling obligations under Article 11 of the WIPO Copyright Treaty adopted on December 20, 1996, and/or similar international agreements.

     e.	Exceptions and Limitations means fair use, fair dealing, and/or any other exception or limitation to Copyright and Similar Rights that applies to Your use of the Licensed Material.

     f.	Licensed Material means the artistic or literary work, database, or other material to which the Licensor applied this Public License.

     g.	Licensed Rights means the rights granted to You subject to the terms and conditions of this Public License, which are limited to all Copyright and Similar Rights that apply to Your use of the Licensed Material and that the Licensor has authority to license.

     h.	Licensor means the individual(s) or entity(ies) granting rights under this Public License.

     i.	NonCommercial means not primarily intended for or directed towards commercial advantage or monetary compensation. For purposes of this Public License, the exchange of the Licensed Material for other material subject to Copyright and Similar Rights by digital file-sharing or similar means is NonCommercial provided there is no payment of monetary compensation in connection with the exchange.

     j.	Share means to provide material to the public by any means or process that requires permission under the Licensed Rights, such as reproduction, public display, public performance, distribution, dissemination, communication, or importation, and to make material available to the public including in ways that members of the public may access the material from a place and at a time individually chosen by them.

     k.	Sui Generis Database Rights means rights other than copyright resulting from Directive 96/9/EC of the European Parliament and of the Council of 11 March 1996 on the legal protection of databases, as amended and/or succeeded, as well as other essentially equivalent rights anywhere in the world.

     l.	You means the individual or entity exercising the Licensed Rights under this Public License. Your has a corresponding meaning.

Section 2 – Scope.

     a.	License grant.

          1. Subject to the terms and conditions of this Public License, the Licensor hereby grants You a worldwide, royalty-free, non-sublicensable, non-exclusive, irrevocable license to exercise the Licensed Rights in the Licensed Material to:

               A. reproduce and Share the Licensed Material, in whole or in part, for NonCommercial purposes only; and

               B. produce, reproduce, and Share Adapted Material for NonCommercial purposes only.

          2. Exceptions and Limitations. For the avoidance of doubt, where Exceptions and Limitations apply to Your use, this Public License does not apply, and You do not need to comply with its terms and conditions.

          3. Term. The term of this Public License is specified in Section 6(a).

          4. Media and formats; technical modifications allowed. The Licensor authorizes You to exercise the Licensed Rights in all media and formats whether now known or hereafter created, and to make technical modifications necessary to do so. The Licensor waives and/or agrees not to assert any right or authority to forbid You from making technical modifications necessary to exercise the Licensed Rights, including technical modifications necessary to circumvent Effective Technological Measures. For purposes of this Public License, simply making modifications authorized by this Section 2(a)(4) never produces Adapted Material.

          5. Downstream recipients.

               A. Offer from the Licensor – Licensed Material. Every recipient of the Licensed Material automatically receives an offer from the Licensor to exercise the Licensed Rights under the terms and conditions of this Public License.

               B. No downstream restrictions. You may not offer or impose any additional or different terms or conditions on, or apply any Effective Technological Measures to, the Licensed Material if doing so restricts exercise of the Licensed Rights by any recipient of the Licensed Material.

          6. No endorsement. Nothing in this Public License constitutes or may be construed as permission to assert or imply that You are, or that Your use of the Licensed Material is, connected with, or sponsored, endorsed, or granted official status by, the Licensor or others designated to receive attribution as provided in Section 3(a)(1)(A)(i).

     b.	Other rights.

          1. Moral rights, such as the right of integrity, are not licensed under this Public License, nor are publicity, privacy, and/or other similar personality rights; however, to the extent possible, the Licensor waives and/or agrees not to assert any such rights held by the Licensor to the limited extent necessary to allow You to exercise the Licensed Rights, but not otherwise.

          2. Patent and trademark rights are not licensed under this Public License.

          3. To the extent possible, the Licensor waives any right to collect royalties from You for the exercise of the Licensed Rights, whether directly or through a collecting society under any voluntary or waivable statutory or compulsory licensing scheme. In all other cases the Licensor expressly reserves any right to collect such royalties, including when the Licensed Material is used other than for NonCommercial purposes.

Section 3 – License Conditions.

Your exercise of the Licensed Rights is expressly made subject to the following conditions.

     a.	Attribution.

          1. If You Share the Licensed Material (including in modified form), You must:

               A. retain the following if it is supplied by the Licensor with the Licensed Material:

                    i.	identification of the creator(s) of the Licensed Material and any others designated to receive attribution, in any reasonable manner requested by the Licensor (including by pseudonym if designated);

                    ii.	a copyright notice;

                    iii. a notice that refers to this Public License;

                    iv.	a notice that refers to the disclaimer of warranties;

                    v.	a URI or hyperlink to the Licensed Material to the extent reasonably practicable;

               B. indicate if You modified the Licensed Material and retain an indication of any previous modifications; and

               C. indicate the Licensed Material is licensed under this Public License, and include the text of, or the URI or hyperlink to, this Public License.

          2. You may satisfy the conditions in Section 3(a)(1) in any reasonable manner based on the medium, means, and context in which You Share the Licensed Material. For example, it may be reasonable to satisfy the conditions by providing a URI or hyperlink to a resource that includes the required information.

          3. If requested by the Licensor, You must remove any of the information required by Section 3(a)(1)(A) to the extent reasonably practicable.

          4. If You Share Adapted Material You produce, the Adapter's License You apply must not prevent recipients of the Adapted Material from complying with this Public License.

Section 4 – Sui Generis Database Rights.

Where the Licensed Rights include Sui Generis Database Rights that apply to Your use of the Licensed Material:

     a.	for the avoidance of doubt, Section 2(a)(1) grants You the right to extract, reuse, reproduce, and Share all or a substantial portion of the contents of the database for NonCommercial purposes only;

     b.	if You include all or a substantial portion of the database contents in a database in which You have Sui Generis Database Rights, then the database in which You have Sui Generis Database Rights (but not its individual contents) is Adapted Material; and

     c.	You must comply with the conditions in Section 3(a) if You Share all or a substantial portion of the contents of the database.
For the avoidance of doubt, this Section 4 supplements and does not replace Your obligations under this Public License where the Licensed Rights include other Copyright and Similar Rights.

Section 5 – Disclaimer of Warranties and Limitation of Liability.

     a.	Unless otherwise separately undertaken by the Licensor, to the extent possible, the Licensor offers the Licensed Material as-is and as-available, and makes no representations or warranties of any kind concerning the Licensed Material, whether express, implied, statutory, or other. This includes, without limitation, warranties of title, merchantability, fitness for a particular purpose, non-infringement, absence of latent or other defects, accuracy, or the presence or absence of errors, whether or not known or discoverable. Where disclaimers of warranties are not allowed in full or in part, this disclaimer may not apply to You.

     b.	To the extent possible, in no event will the Licensor be liable to You on any legal theory (including, without limitation, negligence) or otherwise for any direct, special, indirect, incidental, consequential, punitive, exemplary, or other losses, costs, expenses, or damages arising out of this Public License or use of the Licensed Material, even if the Licensor has been advised of the possibility of such losses, costs, expenses, or damages. Where a limitation of liability is not allowed in full or in part, this limitation may not apply to You.

     c.	The disclaimer of warranties and limitation of liability provided above shall be interpreted in a manner that, to the extent possible, most closely approximates an absolute disclaimer and waiver of all liability.

Section 6 – Term and Termination.

     a.	This Public License applies for the term of the Copyright and Similar Rights licensed here. However, if You fail to comply with this Public License, then Your rights under this Public License terminate automatically.

     b.	Where Your right to use the Licensed Material has terminated under Section 6(a), it reinstates:

          1. automatically as of the date the violation is cured, provided it is cured within 30 days of Your discovery of the violation; or

          2. upon express reinstatement by the Licensor.

     For the avoidance of doubt, this Section 6(b) does not affect any right the Licensor may have to seek remedies for Your violations of this Public License.

     c.	For the avoidance of doubt, the Licensor may also offer the Licensed Material under separate terms or conditions or stop distributing the Licensed Material at any time; however, doing so will not terminate this Public License.

     d.	Sections 1, 5, 6, 7, and 8 survive termination of this Public License.

Section 7 – Other Terms and Conditions.

     a.	The Licensor shall not be bound by any additional or different terms or conditions communicated by You unless expressly agreed.

     b.	Any arrangements, understandings, or agreements regarding the Licensed Material not stated herein are separate from and independent of the terms and conditions of this Public License.

Section 8 – Interpretation.

     a.	For the avoidance of doubt, this Public License does not, and shall not be interpreted to, reduce, limit, restrict, or impose conditions on any use of the Licensed Material that could lawfully be made without permission under this Public License.

     b.	To the extent possible, if any provision of this Public License is deemed unenforceable, it shall be automatically reformed to the minimum extent necessary to make it enforceable. If the provision cannot be reformed, it shall be severed from this Public License without affecting the enforceability of the remaining terms and conditions.

     c.	No term or condition of this Public License will be waived and no failure to comply consented to unless expressly agreed to by the Licensor.

     d.	Nothing in this Public License constitutes or may be interpreted as a limitation upon, or waiver of, any privileges and immunities that apply to the Licensor or You, including from the legal processes of any jurisdiction or authority.

Creative Commons is not a party to its public licenses. Notwithstanding, Creative Commons may elect to apply one of its public licenses to material it publishes and in those instances will be considered the “Licensor.” Except for the limited purpose of indicating that material is shared under a Creative Commons public license or as otherwise permitted by the Creative Commons policies published at creativecommons.org/policies, Creative Commons does not authorize the use of the trademark “Creative Commons” or any other trademark or logo of Creative Commons without its prior written consent including, without limitation, in connection with any unauthorized modifications to any of its public licenses or any other arrangements, understandings, or agreements concerning use of licensed material. For the avoidance of doubt, this paragraph does not form part of the public licenses.

Creative Commons may be contacted at creativecommons.org.
```