README.md

---
base_model: Gryphe/Pantheon-Proto-RP-1.8-30B-A3B
language:
- en
license: apache-2.0
tags:
- instruct
- finetune
- chatml
- axolotl
- roleplay
- llama-cpp
- gguf-my-repo
---

# Triangle104/Pantheon-Proto-RP-1.8-30B-A3B-Q4_K_S-GGUF
This model was converted to GGUF format from [`Gryphe/Pantheon-Proto-RP-1.8-30B-A3B`](https://huggingface.co/Gryphe/Pantheon-Proto-RP-1.8-30B-A3B) 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/Gryphe/Pantheon-Proto-RP-1.8-30B-A3B) for more details on the model.

---
Ever since Qwen 3 released I've been trying to get MoE finetuning to 
work - After countless frustrating days, much code hacking, etc etc I 
finally got a full finetune to complete with reasonable loss values.


I picked the base model for this since I didn't feel like trying to 
fight a reasoning model's training - Maybe someday I'll make a model 
which uses thinking tags for the character's thoughts or something.


This time the recipe focused on combining as many data sources as I 
possibly could, featuring synthetic data from Sonnet 3.5 + 3.7, ChatGPT 
4o and Deepseek. These then went through an extensive rewriting pipeline
 to eliminate common AI cliches, with the hopeful intent of providing 
you a fresh experience.

---
## 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/Pantheon-Proto-RP-1.8-30B-A3B-Q4_K_S-GGUF --hf-file pantheon-proto-rp-1.8-30b-a3b-q4_k_s.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo Triangle104/Pantheon-Proto-RP-1.8-30B-A3B-Q4_K_S-GGUF --hf-file pantheon-proto-rp-1.8-30b-a3b-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/Pantheon-Proto-RP-1.8-30B-A3B-Q4_K_S-GGUF --hf-file pantheon-proto-rp-1.8-30b-a3b-q4_k_s.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo Triangle104/Pantheon-Proto-RP-1.8-30B-A3B-Q4_K_S-GGUF --hf-file pantheon-proto-rp-1.8-30b-a3b-q4_k_s.gguf -c 2048
```