Triangle104/Meissa-Qwen2.5-7B-Instruct-Q4_K_S-GGUF
This model was converted to GGUF format from Orion-zhen/Meissa-Qwen2.5-7B-Instruct
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:
Meissa is designated Lambda Orionis, forms Orion's head, and is a multiple star with a combined apparent magnitude of 3.33. Its name means the "shining one".
This model is fine tuned over writing and role playing datasets (maybe the first on qwen2.5-7b), aiming to enhance model's performance in novel writing and roleplaying.
The model is fine-tuned over Orion-zhen/Qwen2.5-7B-Instruct-Uncensored Training details
I used SFT method. Datasets used are listed below:
anthracite-org/stheno-filtered-v1.1
MinervaAI/Aesir-Preview
Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
anthracite-org/nopm_claude_writing_fixed
Gryphe/Sonnet3.5-Charcard-Roleplay
nothingiisreal/DirtyWritingPrompts
Orion-zhen/tagged-pixiv-novel
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/Meissa-Qwen2.5-7B-Instruct-Q4_K_S-GGUF --hf-file meissa-qwen2.5-7b-instruct-q4_k_s.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo Triangle104/Meissa-Qwen2.5-7B-Instruct-Q4_K_S-GGUF --hf-file meissa-qwen2.5-7b-instruct-q4_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/Meissa-Qwen2.5-7B-Instruct-Q4_K_S-GGUF --hf-file meissa-qwen2.5-7b-instruct-q4_k_s.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo Triangle104/Meissa-Qwen2.5-7B-Instruct-Q4_K_S-GGUF --hf-file meissa-qwen2.5-7b-instruct-q4_k_s.gguf -c 2048
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