d4rkninja/tanpo-fundraising-LoRA
text-generation model by d4rkninja
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Model card & documentation
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PEFT LoRA adapter that specializes LiquidAI/LFM2.5-1.2B-Instruct for fundraising workflows (trained via Unsloth hub id unsloth/LFM2.5-1.2B-Instruct). Creator: d4rkninja Collection: Tanpo — Domain Specialists Tanpo is a family of compact domain-specialized business models for local / edge / inexpensive deployment. Different specialists cover different workflows. Original upstream: LiquidAI/LFM2.5-1.2B-Instruct (1.17B parameters, 32,768-token context, designed for edge/on-device deployment). Fine-tuning: Unsloth-compatible loading of that checkpoint via hub id unsloth/LFM2.5-1.2B-Instruct (LoRA / PEFT). Full eval, examples, and responsible-use notes: d4rkninja/tanpo-fundraising. Delta is calculated from unrounded scores; displayed scores are rounded to one decimal place. Largest overall gain vs base; trailed on only dilutionroundstructure (−22.2 percentage points on that category). Overall still ahead of base; this category is disclosed. Internal DarkLab automated domain evaluation (directional). Held-out fundraising tasks (20). Same prompts and generation config for base…
Read the full model card ↗ · Preview checked 2026-10-29T10:14:47.806Z
Inside the original model card — Document outline
- Tanpo Fundraising (LoRA)
- Adapter settings (from adapterconfig.json)
- Evaluation (summary)
- Load with PEFT
- Related
- License
- Tanpo Family
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Model overview
d4rkninja/tanpo-fundraising-LoRA is a text-generation model repository published by d4rkninja on Hugging Face. The source reports the peft library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-generation
- Library
- peft
- Recent downloads (30 days)
- 0
- Cumulative likes
- 0
- Hugging Face trending score
- 0
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- other
- Access
- Not gated by Hugging Face
- Created
- 2026-09-18T06:24:23.000Z
- Last modified
- 2026-09-18T06:25:08.000Z
Compatibility and lineage
Language coverage was not reported.
Reported base models: LiquidAI/LFM2.5-1.2B-Instruct
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-09-18T06:35:09.247Z. Daily imports are snapshots, not real-time monitoring.
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