metadata

base_model: Locutusque/Apollo-2.0-Llama-3.1-8B
datasets:
  - Locutusque/ApolloRP-2.0-SFT
language:
  - en
library_name: transformers
license: llama3.1
pipeline_tag: text-generation
tags:
  - not-for-all-audiences
  - llama-cpp
  - gguf-my-repo

Triangle104/Apollo-2.0-Llama-3.1-8B-Q5_K_S-GGUF

This model was converted to GGUF format from Locutusque/Apollo-2.0-Llama-3.1-8B using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

Model Details

Fine-tuned Llama-3.1-8B on Locutusque/ApolloRP-2.0-SFT. Results in a good roleplaying language model, that isn't dumb.

Developed by: Locutusque
Model type: Llama3.1
Language(s) (NLP): English
License: Llama 3.1 Community License Agreement

Model Sources [optional]

Demo: https://huggingface.co/spaces/Locutusque/Locutusque-Models

Direct Use

RP/ERP, instruction following, conversation, etc Bias, Risks, and Limitations

This model is completely uncensored - use at your own risk. Recommendations

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. Training Details Training Data

Locutusque/ApolloRP-2.0-SFT

The training data is cleaned from refusals, and "slop". Training Hyperparameters

Training regime: bf16 non-mixed precision

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/Apollo-2.0-Llama-3.1-8B-Q5_K_S-GGUF --hf-file apollo-2.0-llama-3.1-8b-q5_k_s.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Triangle104/Apollo-2.0-Llama-3.1-8B-Q5_K_S-GGUF --hf-file apollo-2.0-llama-3.1-8b-q5_k_s.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/Apollo-2.0-Llama-3.1-8B-Q5_K_S-GGUF --hf-file apollo-2.0-llama-3.1-8b-q5_k_s.gguf -p "The meaning to life and the universe is"

./llama-server --hf-repo Triangle104/Apollo-2.0-Llama-3.1-8B-Q5_K_S-GGUF --hf-file apollo-2.0-llama-3.1-8b-q5_k_s.gguf -c 2048