Instructions to use rexprimematrix/RiShreAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use rexprimematrix/RiShreAI with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="rexprimematrix/RiShreAI", filename="Phi-3-mini-4k-instruct-q4.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use rexprimematrix/RiShreAI with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf rexprimematrix/RiShreAI # Run inference directly in the terminal: llama-cli -hf rexprimematrix/RiShreAI
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf rexprimematrix/RiShreAI # Run inference directly in the terminal: llama-cli -hf rexprimematrix/RiShreAI
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 rexprimematrix/RiShreAI # Run inference directly in the terminal: ./llama-cli -hf rexprimematrix/RiShreAI
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 rexprimematrix/RiShreAI # Run inference directly in the terminal: ./build/bin/llama-cli -hf rexprimematrix/RiShreAI
Use Docker
docker model run hf.co/rexprimematrix/RiShreAI
- LM Studio
- Jan
- Ollama
How to use rexprimematrix/RiShreAI with Ollama:
ollama run hf.co/rexprimematrix/RiShreAI
- Unsloth Studio new
How to use rexprimematrix/RiShreAI with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for rexprimematrix/RiShreAI to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for rexprimematrix/RiShreAI to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for rexprimematrix/RiShreAI to start chatting
- Docker Model Runner
How to use rexprimematrix/RiShreAI with Docker Model Runner:
docker model run hf.co/rexprimematrix/RiShreAI
- Lemonade
How to use rexprimematrix/RiShreAI with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull rexprimematrix/RiShreAI
Run and chat with the model
lemonade run user.RiShreAI-{{QUANT_TAG}}List all available models
lemonade list
| # Python 3.9 image use kar rahe hain | |
| FROM python:3.9 | |
| # Hugging Face permissions setup | |
| RUN useradd -m -u 1000 user | |
| USER user | |
| ENV PATH="/home/user/.local/bin:$PATH" | |
| WORKDIR /app | |
| # Requirements copy karke install karo | |
| COPY --chown=user requirements.txt requirements.txt | |
| RUN pip install --no-cache-dir --upgrade -r requirements.txt | |
| # Baaki code (brain.py aur model) copy karo | |
| COPY --chown=user . /app | |
| # Flask ko port 7860 par expose karo | |
| EXPOSE 7860 | |
| # Command to run the brain | |
| CMD ["python", "brain.py"] |