---
base_model: Delta-Vector/Francois-PE-V2-Huali-12B
datasets:
- PocketDoc/Dans-Personamaxx-VN
- NewEden/LIMARP-Complexity
- NewEden/PIPPA-Mega-Filtered
- NewEden/OpenCAI-ShareGPT
- NewEden/Creative_Writing-Complexity
- NewEden/Light-Novels-Roleplay-Logs-Books-Oh-My-duplicate-turns-removed
- PocketDoc/Dans-Failuremaxx-Adventure-3
- NewEden/Books-V2-ShareGPT
- NewEden/Deepseek-V3-RP-Filtered
- NewEden/BlueSky-10K-Complexity
- NewEden/Final-Alpindale-LNs-ShareGPT
- NewEden/DeepseekRP-Filtered
- NewEden/RP-logs-V2-Experimental
- anthracite-org/kalo_opus_misc_240827
- anthracite-org/kalo_misc_part2
- NewEden/vanilla-backrooms-claude-sharegpt
- NewEden/Storium-Prefixed-Clean
- NewEden/KTO-IF-Dans
- NewEden/KTO-Instruct-Mix
- NewEden/Opus-accepted-hermes-rejected-shuffled
library_name: transformers
tags:
- fine-tuning
- prose
- KTO
- axolotl
- finetune
- roleplaying
- creative-writing
- llama-cpp
- gguf-my-repo
---

# Disya/Francois-PE-V2-Huali-12B-Q5_K_S-GGUF
This model was converted to GGUF format from [`Delta-Vector/Francois-PE-V2-Huali-12B`](https://huggingface.co/Delta-Vector/Francois-PE-V2-Huali-12B) 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/Delta-Vector/Francois-PE-V2-Huali-12B) for more details on the model.

## 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 Disya/Francois-PE-V2-Huali-12B-Q5_K_S-GGUF --hf-file francois-pe-v2-huali-12b-q5_k_s.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo Disya/Francois-PE-V2-Huali-12B-Q5_K_S-GGUF --hf-file francois-pe-v2-huali-12b-q5_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 Disya/Francois-PE-V2-Huali-12B-Q5_K_S-GGUF --hf-file francois-pe-v2-huali-12b-q5_k_s.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo Disya/Francois-PE-V2-Huali-12B-Q5_K_S-GGUF --hf-file francois-pe-v2-huali-12b-q5_k_s.gguf -c 2048
```