Instructions to use tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF 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 tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF:Q4_K_M
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 tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF:Q4_K_M
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 tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF:Q4_K_M
Use Docker
docker model run hf.co/tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF:Q4_K_M
- Ollama
How to use tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF with Ollama:
ollama run hf.co/tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF:Q4_K_M
- Unsloth Desktop
- Pi
How to use tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF with Docker Model Runner:
docker model run hf.co/tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF:Q4_K_M
- Lemonade
How to use tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.MiniCPM5-2B-SFT-Pashto-GGUF-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF:Q4_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF:Q4_K_M
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF:Q4_K_M" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
MiniCPM5-2B-SFT-Pashto-GGUF
GGUF quantizations of nassimjp/MiniCPM5-2B-SFT-Pashto, a fine-tuned version of openbmb/MiniCPM5-2B for Pashto language.
Quant Table
| File | Bits | Est. Size | Use Case |
|---|---|---|---|
| model_f16.gguf | 16 | ~4.6 GB | Reference / re-quantization |
| model_q8_0.gguf | 8 | ~2.4 GB | Max quality, enough RAM |
| model_q6_k.gguf | 6 | ~1.9 GB | High quality |
| model_q5_k_m.gguf | 5 | ~1.6 GB | Balanced |
| model_q5_k_s.gguf | 5 | ~1.6 GB | Balanced, smaller |
| model_q4_k_m.gguf | 4 | ~1.4 GB | Recommended |
| model_q4_k_s.gguf | 4 | ~1.3 GB | Lower RAM |
| model_q3_k_l.gguf | 3 | ~1.1 GB | Low RAM |
| model_q3_k_m.gguf | 3 | ~1.0 GB | Low RAM |
| model_q3_k_s.gguf | 3 | ~0.9 GB | Minimum quality |
| model_q2_k.gguf | 2 | ~0.7 GB | Very low RAM only |
VRAM / RAM Requirements
| Quant | RAM |
|---|---|
| Q8_0 | ~3 GB |
| Q4_K_M | ~2 GB |
| Q2_K | ~1.5 GB |
Usage
llama.cpp
./llama-cli -m model_q4_k_m.gguf -p "Your prompt here" -n 256
llama-cpp-python
from llama_cpp import Llama
llm = Llama(model_path="model_q4_k_m.gguf")
output = llm("Your prompt here", max_tokens=256)
print(output["choices"][0]["text"])
LM Studio
Download any .gguf file and load directly in LM Studio.
Ollama
ollama run hf.co/tinyopsec/MiniCPM5-2B-SFT-Pashto-GGUF:Q4_K_M
Notes
- Architecture:
LlamaForCausalLM - Fine-tuned for Pashto (پښتو) language
- Based on MiniCPM5-2B with hybrid reasoning (Think / No-Think modes)
- For llama.cpp, recommended:
--min-p 0.0to avoid repetition
- Downloads last month
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Hardware compatibility
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