---
license: llama3
language:
- en
base_model: SicariusSicariiStuff/Dusk_Rainbow
tags:
- llama-cpp
- gguf-my-repo
---

# Triangle104/Dusk_Rainbow-Q4_K_S-GGUF
This model was converted to GGUF format from [`SicariusSicariiStuff/Dusk_Rainbow`](https://huggingface.co/SicariusSicariiStuff/Dusk_Rainbow) 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/SicariusSicariiStuff/Dusk_Rainbow) for more details on the model.

---
Censorship level: Very low 

9.1 / 10 (10 completely uncensored)

Intended use: Creative Writing, General tasks.

This model is the result of training a fraction (16M tokens) of the testing data Intended for LLAMA-3_8B_Unaligned's upcoming beta.
The base model is a merge of merges, made by Invisietch's and named EtherealRainbow-v0.3-8B.
 The name for this model reflects the base that was used for this 
finetune while hinting a darker, and more uncensored aspects associated 
with the nature of the LLAMA-3_8B_Unaligned project.

As a result of the unique data added, this model has an exceptional 
adherence to instructions about paragraph length, and to the story 
writing prompt. I would like to emphasize, no ChatGPT \ Claude was used for any of the additional data I added in this finetune. The goal is to eventually have a model with a minimal amount of slop, this cannot be reliably done by relying on API models, which pollute datasets with their bias and repetitive words.

---
## 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/Dusk_Rainbow-Q4_K_S-GGUF --hf-file dusk_rainbow-q4_k_s.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo Triangle104/Dusk_Rainbow-Q4_K_S-GGUF --hf-file dusk_rainbow-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/Dusk_Rainbow-Q4_K_S-GGUF --hf-file dusk_rainbow-q4_k_s.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo Triangle104/Dusk_Rainbow-Q4_K_S-GGUF --hf-file dusk_rainbow-q4_k_s.gguf -c 2048
```