README.md

---
license: apache-2.0
base_model: allura-org/Qwen2.5-32b-RP-Ink
tags:
- roleplay
- conversational
- llama-cpp
- gguf-my-repo
language:
- en
---

# Triangle104/Qwen2.5-32b-RP-Ink-Q4_K_S-GGUF
This model was converted to GGUF format from [`allura-org/Qwen2.5-32b-RP-Ink`](https://huggingface.co/allura-org/Qwen2.5-32b-RP-Ink) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/allura-org/Qwen2.5-32b-RP-Ink) for more details on the model.

---
Model details:
-
A roleplay-focused LoRA finetune of Qwen 2.5 32b Instruct. Methodology and hyperparams inspired by SorcererLM and Slush.
Yet another model in the Ink series, following in the footsteps of the Nemo one

Testimonials
-
whatever I tested was crack [...] It's got some refreshingly good prose, that's for sure

- TheLonelyDevil

The NTR is fantastic with this tune, lots of good gooning to be had. [...] Description and scene setting prose flows smoothly in comparison to larger models.

- TonyTheDeadly

This 32B handles complicated scenarios well, compared to a lot of 70Bs I've tried. Characters are portrayed accurately.

- Severian

From the very limited testing I did, I quite like this. [...] I really like the way it writes. Granted, I'm completely shitfaced right now, but I'm pretty sure it's good.

- ALK

[This model portrays] my character card almost exactly the way that I write them. It's a bit of a dream to get that with many of the current LLM.

- ShotMisser64

Dataset
-
The worst mix of data you've ever seen. Like, seriously, you do not want to see the things that went into this model. It's bad.

"this is like washing down an adderall with a bottle of methylated rotgut" - inflatebot

Recommended Settings
-
Chat template: ChatML

Recommended samplers (not the be-all-end-all, try some on your own!):
-
Temp 0.85 / Top P 0.8 / Top A 0.3 / Rep Pen 1.03

Your samplers can go here! :3

Hyperparams

General
-
Epochs = 1

LR = 6e-5

LR Scheduler = Cosine

Optimizer = Paged AdamW 8bit

Effective batch size = 16

LoRA
-
Rank = 16

Alpha = 32

Dropout = 0.25 (Inspiration: Slush)

Credits
-
Humongous thanks to the people who created the data. I would credit you all, but that would be cheating ;)
Big thanks to all Allura members, for testing and emotional support ilya /platonic
especially to inflatebot who made the model card's image :3
Another big thanks to all the members of the ArliAI Discord server for testing! All of the people featured in the testimonials are from there :3

---
## Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)

```bash
brew install llama.cpp

```
Invoke the llama.cpp server or the CLI.

### CLI:
```bash
llama-cli --hf-repo Triangle104/Qwen2.5-32b-RP-Ink-Q4_K_S-GGUF --hf-file qwen2.5-32b-rp-ink-q4_k_s.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo Triangle104/Qwen2.5-32b-RP-Ink-Q4_K_S-GGUF --hf-file qwen2.5-32b-rp-ink-q4_k_s.gguf -c 2048
```

Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.
```
git clone https://github.com/ggerganov/llama.cpp
```

Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
```
cd llama.cpp && LLAMA_CURL=1 make
```

Step 3: Run inference through the main binary.
```
./llama-cli --hf-repo Triangle104/Qwen2.5-32b-RP-Ink-Q4_K_S-GGUF --hf-file qwen2.5-32b-rp-ink-q4_k_s.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo Triangle104/Qwen2.5-32b-RP-Ink-Q4_K_S-GGUF --hf-file qwen2.5-32b-rp-ink-q4_k_s.gguf -c 2048
```