- Libraries
- Transformers
How to use musamrc/model_256_256 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="musamrc/model_256_256")
messages = [
{"role": "user", "content": "Who are you?"},
]
pipe(messages) # pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("musamrc/model_256_256", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use musamrc/model_256_256 with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf musamrc/model_256_256:Q8_0
# Run inference directly in the terminal:
llama cli -hf musamrc/model_256_256:Q8_0
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf musamrc/model_256_256:Q8_0
# Run inference directly in the terminal:
llama cli -hf musamrc/model_256_256:Q8_0
Use pre-built binary
# 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 musamrc/model_256_256:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf musamrc/model_256_256:Q8_0
Build from source code
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 musamrc/model_256_256:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf musamrc/model_256_256:Q8_0
Use Docker
docker model run hf.co/musamrc/model_256_256:Q8_0
- Llama new
- LM Studio
- Jan
- Ollama
How to use musamrc/model_256_256 with Ollama:
ollama run hf.co/musamrc/model_256_256:Q8_0
- Unsloth Desktop
- Docker Model Runner
How to use musamrc/model_256_256 with Docker Model Runner:
docker model run hf.co/musamrc/model_256_256:Q8_0
- Lemonade
How to use musamrc/model_256_256 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/
lemonade pull musamrc/model_256_256:Q8_0
Run and chat with the model
lemonade run user.model_256_256-Q8_0
List all available models
lemonade list
- Atomic Chat
