ReWiz
Collection
The ReWiz series is based on a subset of data from 3 different data sets, which has been used for fine tuning. โข 18 items โข Updated โข 1
How to use theprint/ReWiz-Gemma2-9B with Transformers:
# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("theprint/ReWiz-Gemma2-9B", device_map="auto")How to use theprint/ReWiz-Gemma2-9B with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf theprint/ReWiz-Gemma2-9B:Q4_K_M # Run inference directly in the terminal: llama cli -hf theprint/ReWiz-Gemma2-9B:Q4_K_M
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf theprint/ReWiz-Gemma2-9B:Q4_K_M # Run inference directly in the terminal: llama cli -hf theprint/ReWiz-Gemma2-9B:Q4_K_M
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf theprint/ReWiz-Gemma2-9B:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf theprint/ReWiz-Gemma2-9B:Q4_K_M
docker model run hf.co/theprint/ReWiz-Gemma2-9B:Q4_K_M
How to use theprint/ReWiz-Gemma2-9B with Ollama:
ollama run hf.co/theprint/ReWiz-Gemma2-9B:Q4_K_M
How to use theprint/ReWiz-Gemma2-9B with Docker Model Runner:
docker model run hf.co/theprint/ReWiz-Gemma2-9B:Q4_K_M
How to use theprint/ReWiz-Gemma2-9B with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull theprint/ReWiz-Gemma2-9B:Q4_K_M
lemonade run user.ReWiz-Gemma2-9B-Q4_K_M
lemonade list
\n\n### Instruction:\n### Response:\nThis gemma2 model was trained 2x faster with Unsloth and Huggingface's TRL library.