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ali-thowfeek/Charty-1B-GGUF
Charty-1B-GGUF is a text generation model from ali-thowfeek. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as other.
Quantized GGUF versions of Charty-1B, a compact text-to-Mermaid diagram generation model fine-tuned from LFM2.5-1.2B-Instruct. Designed for on-device, mobile, and CPU-only inference.
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.gguf4.3 GB · 100%
From the Hugging Face model README
Quantized GGUF versions of Charty-1B, a compact text-to-Mermaid diagram generation model fine-tuned from LFM2.5-1.2B-Instruct. Designed for on-device, mobile, and CPU-only inference.
For the original 16-bit safetensors, see ali-thowfeek/Charty-1B.
| File | Quantization | Size (approx.) | Quality | Best For |
|---|---|---|---|---|
Charty-1B-F16.gguf | F16 (full) | ~2.3 GB | ★★★★★ Maximum | GPU inference, maximum fidelity |
Charty-1B-Q8_0.gguf | Q8_0 | ~1.2 GB | ★★★★☆ Near-lossless | Balanced CPU / edge deployment |
Charty-1B-Q4_K_M.gguf | Q4_K_M | ~0.7 GB | ★★★☆☆ Good | Mobile phones, low-RAM devices. See demo: Charty-1B-Q4_K_M running on mobile phone |
| Field | Value |
|---|---|
| Base model | unsloth/LFM2.5-1.2B-Instruct |
| Architecture | LFM2 (hybrid: 10 double-gated LIV convolution blocks + 6 GQA attention blocks) |
| Parameters | 1.17B |
| Context length | 32,768 tokens |
| Vocabulary size | 65,536 |
| Fine-tuning method | LoRA (SFT) via Unsloth + Hugging Face TRL |
| Training dataset | ali-thowfeek/text-to-mermaid (3,837 examples) |
| Developed by | ali-thowfeek |
This model ships with Unsloth's fixed Jinja chat template embedded in the GGUF versions and is applied automatically by llama.cpp with --jinja.
Generate Mermaid diagram syntax (flowcharts, sequence, class, state, ER, Gantt, pie, git graphs, mindmaps, quadrant charts, …) from plain-text prompts. Run on low-end hardware: mobile phones, edge devices, laptops, embedded systems. Power apps that need offline, private, diagram-as-code generation.
Input (user prompt):
Create a flowchart showing the user login process with MFA verification.
Output (model response):
graph TD
A[User Visits Login Page] --> B[Enter Credentials]
B --> C{Credentials Valid?}
C -->|No| D[Show Error Message]
D --> B
C -->|Yes| E[Send MFA Code]
E --> F[Enter MFA Code]
F --> G{MFA Valid?}
G -->|No| H[Show MFA Error]
H --> F
G -->|Yes| I[Grant Access]
The model outputs only the Mermaid syntax code. No wrapping text, no mermaid fences.
Recommended Generation Parameters
| Parameter | Value |
|---|---|
| temperature | 0.1 |
| top_k | 50 |
| top_p | 0.1 |
| repetition_penalty | 1.05 |
| Detail | Value |
|---|---|
| Framework | Unsloth + Hugging Face TRL |
| Method | LoRA Supervised Fine-Tuning (SFT), merged into full weights |
| Dataset | ali-thowfeek/text-to-mermaid |
| Dataset size | 3,837 examples |
| Dataset source | Derived from Celiadraw/text-to-mermaid-2, cleaned, reworded, and validated against Mermaid v11 (core) |
| Validation | 100% of training examples produce valid Mermaid v11 core syntax |
| Output format | Raw Mermaid syntax only (no markdown fences, no explanations) |
This model is a derivative work of LFM2.5-1.2B-Instruct by Liquid AI and is released under the LFM Open License v1.0.
Key terms:
See the full LICENSE file in this repository for complete terms.
If you use this model, please cite the base model and this work:
@article{liquidai2025lfm2,
title = {LFM2 Technical Report},
author = {Liquid AI},
journal = {arXiv preprint arXiv:2511.23404},
year = {2025}
}
@misc{thowfeek2026charty,
title = {Charty-1B: A Text-to-Mermaid Diagram Generation Model},
author = {ali-thowfeek},
year = {2026},
url = {https://huggingface.co/ali-thowfeek/Charty-1B}
}