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ArkAiLab-Adl/llama-nexora-vector-v0.1
llama-nexora-vector-v0.1 is a text generation model from ArkAiLab-Adl. Use it when you need the model to write or continue text. The card lists the license as llama3.2.
<p align="center" <img src="https://huggingface.co/ArkAiLab-Adl/llama-nexora-vector-v0.1/resolve/main/assets/llama-nexora-vector.jpg" alt="llama-nexora-vector"/ </p
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From the Hugging Face model README
llama-nexora-vector-v0.1 is an experimental text-to-vector model from the Llama-Nexora family that generates structured SVG graphics from natural language prompts. It is an improved iteration of nexora-vector-v0.1, built on Meta's Llama 3.2 1B Instruct base model and fine-tuned using the Unsloth library. This is a beta release intended for research, prototyping, and early-stage development workflows only.
llama-nexora-vector-v0.1 is a supervised fine-tuned language model adapted specifically to generate structured vector graphics in SVG format from natural language instructions. It builds upon the foundation established by nexora-vector-v0.1, switching the base architecture to Meta's Llama 3.2 1B Instruct and leveraging the Unsloth training library for improved efficiency and output quality.
This release is in beta and is scoped to research, experimentation, and early-stage design tooling. All outputs should be validated before use in any downstream pipeline.
llama-nexora-vector-v0.1 is the inaugural model of the Llama-Nexora family — a dedicated branch of Nexora models built on the Meta Llama architecture. The Llama-Nexora family is a focused effort under ArkAiLabs to develop creative, efficient, and practical open AI systems grounded in the Llama ecosystem.
While the original Nexora series (e.g., nexora-vector-v0.1) explored text-to-vector generation on alternative base architectures, the Llama-Nexora family represents a deliberate pivot toward Meta's open model stack — prioritizing accessibility, community compatibility, and efficient fine-tuning via tools like Unsloth.
The Llama-Nexora family will continue to grow with future models targeting improved SVG generation, richer creative outputs, and broader design tooling applications.
Compared to nexora-vector-v0.1:
| Property | Details |
|---|---|
| Model Name | llama-nexora-vector-v0.1 |
| Model Family | Llama-Nexora |
| Model Type | Text-to-SVG (Causal Language Model) |
| Base Model | unsloth/Llama-3.2-1B-Instruct |
| Previous Version | nexora-vector-v0.1 |
| Training Framework | Unsloth |
| Fine-tuning Method | Supervised Fine-Tuning (SFT) |
| Dataset | Custom curated SVG instruction dataset |
| Output Format | SVG |
| Release Status | Beta |
| License | Llama 3.2 Community License |
llama-nexora-vector-v0.1 is designed to translate textual instructions into structured SVG code. The model is best suited for:
Tip: The model performs best with concise, clearly scoped prompts focused on simple visual compositions.
This is an early-stage beta release. Users should be aware of the following constraints before integrating the model:
The model is built on Llama 3.2 1B Instruct and fine-tuned using the Unsloth library to improve structured SVG output generation efficiency and quality.
| Parameter | Details |
|---|---|
| Base Model | unsloth/Llama-3.2-1B-Instruct |
| Fine-tuning Method | Supervised Fine-Tuning (SFT) |
| Training Library | Unsloth |
| Dataset Composition | Custom curated SVG instruction dataset |
| Training Objective | Structured output generation for SVG formats |
Note: Unsloth enables significantly faster training with lower GPU memory usage compared to standard fine-tuning workflows, making this model more accessible to the broader research community.
To get the best results from llama-nexora-vector-v0.1:
llama-nexora-vector-v0.1 has not yet undergone formal benchmark evaluation. Current assessment is qualitative, based on manual testing of SVG generation tasks.
Planned evaluation metrics for future releases include:
| Metric | Description |
|---|---|
| SVG Validity Rate | Percentage of outputs that are parseable, valid SVG |
| Structural Correctness | Adherence to SVG schema and element hierarchy |
| Prompt Adherence | Alignment between user intent and generated output |
| Visual Consistency | Stability of outputs across similar prompts |
Developers integrating llama-nexora-vector-v0.1 should account for the following risks:
Recommendation: Implement downstream validation layers and SVG syntax checking before any rendering or integration. Human review is recommended for all generated content.
The following improvements are planned for upcoming versions of the Llama-Nexora family:
Join the community for updates, feedback, and discussion. Community feedback, testing, and contributions are welcome — this project will continue evolving through open research and real-world experimentation.
This model is released under the Llama 3.2 Community License.
Use of this model is governed by the Llama 3.2 Community License Agreement. Please review the license terms before use, modification, or distribution.
llama-nexora-vector-v0.1 is built upon Llama 3.2 1B Instruct by Meta. Training was made efficient and accessible through the Unsloth library. This work builds directly on the foundation of nexora-vector-v0.1. We thank the open-source AI community for their continued contributions that make projects like this possible.
Nexora is an experimental AI initiative under ArkAiLabs, focused on building lightweight, practical, and creative AI systems for real-world applications. The Nexora Vector series represents our exploration into AI-assisted vector graphics generation.
The Llama-Nexora family is a dedicated branch within Nexora, built on the Meta Llama architecture — focused on creative, efficient, and practical open AI systems that are accessible to the broader community.