Temis
Collection
25 items • Updated
How to use neopolita/qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16 with Transformers:
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("neopolita/qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16", device_map="auto")How to use neopolita/qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16 with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf neopolita/qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16:F16 # Run inference directly in the terminal: llama cli -hf neopolita/qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16:F16
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf neopolita/qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16:F16 # Run inference directly in the terminal: llama cli -hf neopolita/qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16:F16
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf neopolita/qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16:F16 # Run inference directly in the terminal: ./llama-cli -hf neopolita/qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16:F16
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf neopolita/qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf neopolita/qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16:F16
docker model run hf.co/neopolita/qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16:F16
How to use neopolita/qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16 with Ollama:
ollama run hf.co/neopolita/qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16:F16
How to use neopolita/qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16 with Docker Model Runner:
docker model run hf.co/neopolita/qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16:F16
How to use neopolita/qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16 with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull neopolita/qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16:F16
lemonade run user.qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16-F16
lemonade list
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf neopolita/qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16:F16# Run inference directly in the terminal:
llama cli -hf neopolita/qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16:F16# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf neopolita/qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16:F16# Run inference directly in the terminal:
./llama-cli -hf neopolita/qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16:F16git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf neopolita/qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16:F16# Run inference directly in the terminal:
./build/bin/llama-cli -hf neopolita/qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16:F16docker model run hf.co/neopolita/qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16:F16This qwen2 model was trained 2x faster with Unsloth and Huggingface's TRL library.
16-bit
Install (macOS, Linux)
# Start a local OpenAI-compatible server with a web UI: llama serve -hf neopolita/qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16:F16# Run inference directly in the terminal: llama cli -hf neopolita/qwen-2_5-1_5b-bnb-4bit-law-merged-gguf-f16:F16