Triangle104/Phi-3.5-mini-TitanFusion-0.1-Q4_K_M-GGUF
This model was converted to GGUF format from bunnycore/Phi-3.5-mini-TitanFusion-0.1
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:
This is a merged pre-trained language model created using the TIES merge method. It is based on the microsoft/Phi-3.5-mini-instruct model and incorporates the knowledge and capabilities of the nbeerbower/phi3.5-gutenberg-4B and ArliAI/Phi-3.5-mini-3.8B-ArliAI-RPMax-v1.1 models.
Capabilities: Roleplay: The model can engage in role-playing scenarios, taking on different personas and responding to prompts in a character-appropriate manner. Creative Writing: It can assist in creative writing tasks, such as brainstorming ideas, generating plotlines, or developing characters. Reasoning: The model can reason about information and draw conclusions based on the data it has been trained on. This is a merge of pre-trained language models created using mergekit.
Merge Details Merge Method This model was merged using the TIES merge method using microsoft/Phi-3.5-mini-instruct as a base.
Models Merged The following models were included in the merge:
nbeerbower/phi3.5-gutenberg-4B ArliAI/Phi-3.5-mini-3.8B-ArliAI-RPMax-v1.1 Configuration The following YAML configuration was used to produce this model:
models:
- model: ArliAI/Phi-3.5-mini-3.8B-ArliAI-RPMax-v1.1 parameters: weight: 1
- model: nbeerbower/phi3.5-gutenberg-4B parameters: weight: 1
merge_method: ties base_model: microsoft/Phi-3.5-mini-instruct parameters: density: 1 normalize: true int8_mask: true dtype: bfloat16
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/Phi-3.5-mini-TitanFusion-0.1-Q4_K_M-GGUF --hf-file phi-3.5-mini-titanfusion-0.1-q4_k_m.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo Triangle104/Phi-3.5-mini-TitanFusion-0.1-Q4_K_M-GGUF --hf-file phi-3.5-mini-titanfusion-0.1-q4_k_m.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/Phi-3.5-mini-TitanFusion-0.1-Q4_K_M-GGUF --hf-file phi-3.5-mini-titanfusion-0.1-q4_k_m.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo Triangle104/Phi-3.5-mini-TitanFusion-0.1-Q4_K_M-GGUF --hf-file phi-3.5-mini-titanfusion-0.1-q4_k_m.gguf -c 2048
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Base model
bunnycore/Phi-3.5-mini-TitanFusion-0.1Collections including Triangle104/Phi-3.5-mini-TitanFusion-0.1-Q4_K_M-GGUF
Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard52.280
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard35.450
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard6.190
- acc_norm on GPQA (0-shot)Open LLM Leaderboard10.850
- acc_norm on MuSR (0-shot)Open LLM Leaderboard15.800
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard31.180