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---
base_model: DavidAU/Llama-3.1-1million-ctx-Dark-Planet-v1.01-8B
library_name: transformers
tags:
- mergekit
- merge
- llama-cpp
- gguf-my-repo
---
# Triangle104/Llama-3.1-1million-ctx-Dark-Planet-v1.01-8B-Q4_K_M-GGUF
This model was converted to GGUF format from [`DavidAU/Llama-3.1-1million-ctx-Dark-Planet-v1.01-8B`](https://huggingface.co/DavidAU/Llama-3.1-1million-ctx-Dark-Planet-v1.01-8B) 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/DavidAU/Llama-3.1-1million-ctx-Dark-Planet-v1.01-8B) for more details on the model.
---
This model was converted to Nvidia's new "UltraLong8B" long context Llama 3.1 model structure (https://huggingface.co/nvidia/Llama-3.1-8B-UltraLong-1M-Instruct)
which allowed full transfer of "Dark Planet 8B" in all it's "glory" so
to speak. Due to Nvidia's structure, the new Dark Planet has attained
far greater long generation not only
in terms of context, but also coherence too. There is a also a bump in
overall performance as well.
This model has been designed to be relatively bullet proof and
operates with all parameters, including temp settings from 0 to 5.
It is an extraordinary compressed model, with a very low perplexity level (lower than Meta Llama3 Instruct).
It is for any writing, fiction or roleplay activity.
It requires Llama 3 template and/or "Command-R" template.
Suggest a context window of at least 8k, 16K is better... as this model will generate long outputs unless you set a hard limit.
Likewise, as this is an instruct model - the more instructions in
your prompt and/or system prompt - the greater the output quality.
IE: Less "guessing" equals far higher quality.
---
## 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/Llama-3.1-1million-ctx-Dark-Planet-v1.01-8B-Q4_K_M-GGUF --hf-file llama-3.1-1million-ctx-dark-planet-v1.01-8b-q4_k_m.gguf -p "The meaning to life and the universe is"
```
### Server:
```bash
llama-server --hf-repo Triangle104/Llama-3.1-1million-ctx-Dark-Planet-v1.01-8B-Q4_K_M-GGUF --hf-file llama-3.1-1million-ctx-dark-planet-v1.01-8b-q4_k_m.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/Llama-3.1-1million-ctx-Dark-Planet-v1.01-8B-Q4_K_M-GGUF --hf-file llama-3.1-1million-ctx-dark-planet-v1.01-8b-q4_k_m.gguf -p "The meaning to life and the universe is"
```
or
```
./llama-server --hf-repo Triangle104/Llama-3.1-1million-ctx-Dark-Planet-v1.01-8B-Q4_K_M-GGUF --hf-file llama-3.1-1million-ctx-dark-planet-v1.01-8b-q4_k_m.gguf -c 2048
```
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