d4rkninja/tanpo-deals-GGUF overview
Tanpo Deals GGUF GGUF quantizations of d4rkninja/tanpo deals https://huggingface.co/d4rkninja/tanpo deals for local runtimes llama.cpp , LM Studio , and other …
Runs locally from ~572.5 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| tanpo-deals.Q3_K_M.gguf | GGUF | GGUF | 572.5 MB | Download |
| tanpo-deals.Q4_K_M.gguf | GGUF | GGUF | 697.0 MB | Download |
| tanpo-deals.Q4_K_S.gguf | GGUF | GGUF | 668.0 MB | Download |
| tanpo-deals.Q5_K_M.gguf | GGUF | GGUF | 804.3 MB | Download |
| tanpo-deals.Q5_K_S.gguf | GGUF | GGUF | 787.0 MB | Download |
| tanpo-deals.Q8_0.gguf | GGUF | GGUF | 1.16 GB | Download |
Model Details
| Model ID | d4rkninja/tanpo-deals-GGUF |
|---|---|
| Author | d4rkninja |
| Pipeline | text-generation |
| License | other |
| Base model | LiquidAI/LFM2.5-1.2B-Instruct |
| Last modified | 2026-09-18T17:46:24.000Z |
Model README
---
base_model: LiquidAI/LFM2.5-1.2B-Instruct
language:
- en
license: other
license_name: lfm-1.0
pipeline_tag: text-generation
tags:
- gguf
- llama.cpp
- deals
- sales
- tanpo
- text-generation
---
Tanpo Deals (GGUF)
GGUF quantizations of d4rkninja/tanpo-deals for local runtimes (llama.cpp, LM Studio, and other GGUF-compatible tools).
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).
A compact B2B deal-closing and channel/distributor specialist (~1.2B) for qualification, objections, proposals, and partner motions — built for local and inexpensive deployment.
Available quantizations
On-disk sizes from the live Hugging Face file listing (MB, rounded from bytes). Disk size ≠ peak RAM/VRAM at runtime.
| File | Size |
|---|---:|
| tanpo-deals.Q3_K_M.gguf | 600 MB |
| tanpo-deals.Q4_K_S.gguf | 700 MB |
| tanpo-deals.Q4_K_M.gguf | 731 MB — suggested everyday |
| tanpo-deals.Q5_K_S.gguf | 825 MB |
| tanpo-deals.Q5_K_M.gguf | 843 MB |
| tanpo-deals.Q8_0.gguf | 1246 MB |
Suggested everyday file: tanpo-deals.Q4_K_M.gguf
Evaluation (summary)
| Model | Rubric overall |
|---|---:|
| Base | 87.9% |
| Fine-tune | 95.2% |
| Delta | +7.3 percentage points |
Full methodology on the merged model card. Artifacts: evaluation/. Quantization can change behavior slightly vs BF16 merged weights.
Running locally
- Download
tanpo-deals.Q4_K_M.gguf(or another quant above). - Open it in LM Studio or run with llama.cpp (use a build that supports LFM2 / the model architecture).
- Keep prompts in the deals domain; review consequential outputs with a human.
No separate LoRA step is required — these are standalone GGUF files of the merged specialist.
Related
- Merged Transformers: d4rkninja/tanpo-deals
- LoRA: d4rkninja/tanpo-deals-LoRA
Responsible Use
Not legal, tax, or financial advice. Humans must review contracts, pricing commitments, and partner terms. Do not use for fraud, deception, or unauthorized access.
License
license: other / license_name: lfm-1.0
Tanpo merged and GGUF weights are derivatives of LiquidAI/LFM2.5-1.2B-Instruct under the LFM Open License v1.0 (including the commercial Threshold of approximately $10M annual revenue). See the base model card and its LICENSE file. Credit: LiquidAI. Do not treat this stack as Apache-2.0.
Tanpo Family
Tanpo is a family of compact domain-specialized models for focused business workflows.
This specialist is available as:
- Merged:
d4rkninja/tanpo-deals - LoRA:
d4rkninja/tanpo-deals-LoRA - GGUF:
d4rkninja/tanpo-deals-GGUF
Browse all Tanpo specialists: Tanpo — Domain Specialists
Run d4rkninja/tanpo-deals-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models