Instructions to use rexprimematrix/RiShreAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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

RiShreAI

File size: 505 Bytes

79c98ca

# 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"]