d4rkninja/tanpo-fundraising

TEXT GENERATIONPricing:Input $0.04 / Cached $0.008 / Output $0.08Concurrent Unit Cost:1Model Size:1.2BQuant:BF16Context Size:32kPublished:Sep 18, 2026License:otherArchitecture:Transformer Featherless Exclusive Cold

d4rkninja/tanpo-fundraising is a 1.2 billion parameter language model, fine-tuned from LiquidAI/LFM2.5-1.2B-Instruct, specifically designed as a founder fundraising specialist. It excels at generating investor pitches, narrative arcs, use-of-funds drafts, and diligence Q&A. Optimized for local and inexpensive deployment, this model provides specialized assistance for various fundraising workflows.

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Overview

d4rkninja/tanpo-fundraising is a compact, 1.2 billion parameter language model derived from LiquidAI/LFM2.5-1.2B-Instruct. It is a specialized model within the Tanpo family, focusing exclusively on founder fundraising workflows rather than being a general-purpose or frontier model. The model was fine-tuned using LoRA (PEFT) via Unsloth, with its weights merged into this repository.

Key Capabilities

  • Investor Communications: Generates investor pitch openers, narrative arcs, and framing for presentations.
  • Financial Planning: Assists with drafting 'ask' and 'use-of-funds' tied to milestones, burn rate, and runway.
  • Diligence & Updates: Helps draft responses for diligence/objection Q&A and monthly investor updates.
  • Market & Traction: Supports crafting traction stories, market positioning, and 'why now' framing.

Performance & Training

Internal automated domain evaluation (DarkLab harness) shows tanpo-fundraising achieving 95.2% overall, an +11.1 percentage point improvement over the base LFM2.5-1.2B-Instruct model (84.2%). It was trained on the d4rkninja/tanpo-fundraising-sft dataset, comprising approximately 10,000 chat SFT examples. While highly specialized, its ~1.2B scale means it has limited world knowledge and long-horizon reasoning compared to larger models. It is not designed for legal or investment advice.

Best For

  • Founders seeking assistance with investor-facing content.
  • Teams requiring private, low-cost inference for fundraising-specific text generation.
  • Drafting non-legal round-structure language.

Not Designed For

  • Providing legal or investment advice.
  • General coding or non-fundraising chat.
  • Tasks requiring extensive world knowledge or complex reasoning beyond its specialized domain.

Finetunes
3 models