Triangle104/Llama-3.1-1million-ctx-Dark-Planet-v1.01-8B-Q8_0-GGUF

This model was converted to GGUF format from DavidAU/Llama-3.1-1million-ctx-Dark-Planet-v1.01-8B using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

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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.

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Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo Triangle104/Llama-3.1-1million-ctx-Dark-Planet-v1.01-8B-Q8_0-GGUF --hf-file llama-3.1-1million-ctx-dark-planet-v1.01-8b-q8_0.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Triangle104/Llama-3.1-1million-ctx-Dark-Planet-v1.01-8B-Q8_0-GGUF --hf-file llama-3.1-1million-ctx-dark-planet-v1.01-8b-q8_0.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps 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-Q8_0-GGUF --hf-file llama-3.1-1million-ctx-dark-planet-v1.01-8b-q8_0.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-Q8_0-GGUF --hf-file llama-3.1-1million-ctx-dark-planet-v1.01-8b-q8_0.gguf -c 2048