Instructions to use emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-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 emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-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 emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-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 emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-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 emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-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 emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-GGUF:Q4_K_M
Use Docker
docker model run hf.co/emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-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": "emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-GGUF:Q4_K_M
- Ollama
How to use emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-GGUF with Ollama:
ollama run hf.co/emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-GGUF:Q4_K_M
- Unsloth Studio
How to use emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-GGUF 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 emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-GGUF 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 emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-GGUF to start chatting
- Pi
How to use emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-GGUF:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- OpenClaw new
How to use emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-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 "emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-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"
- Docker Model Runner
How to use emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-GGUF with Docker Model Runner:
docker model run hf.co/emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-GGUF:Q4_K_M
- Lemonade
How to use emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-GGUF-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-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 emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-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 emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat
Base Model: Qwen/Qwen3.6-35B-A3B
Orijinal model: AlicanKiraz0/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model
Alican Kiraz'a, bu modeli bize kazandırdığı için teşekkür ederim. Tüketici ekran kartlarında model çalıştırmak isteyenler, benim gibi, gguf formatında çalıştırabilsin diye dönüştürdüm. Model ile ilgili bütün bilgiler, modelin sahibinin deposunda mevcuttur.
quantized levels
- Q4
- Q5
- Q6
- Q8
Model; finans ile ilgili eğitim ve genel bilgilendirme amaçlı eğitilmiş bir modeldir.
Model Bilgisi / Model Info
| Alan | Bilgi |
|---|---|
| Model Adı | Mihenk-LLM v2 GGUF |
| Orijinal Model | Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model |
| Yazar | Alican Kiraz |
| Format | GGUF (llama.cpp) |
| Lisans | Apache 2.0 |
Bu repo, orijinal modelin GGUF formatına dönüştürülmüş halidir.
Atıf / Citation
@model{MihenkLLMv2,
author = {Alican Kiraz},
title = {Mihenk-LLM v2: A Fine-tuned Qwen3.6-35B-A3B Model for Turkish Financial Reasoning},
year = {2026},
publisher = {Hugging Face},
url = {https://huggingface.co/AlicanKiraz0/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model}
}
Disclaimer: Bu model araştırma, eğitim ve genel bilgilendirme amaçlıdır. Modelin çıktıları yatırım tavsiyesi değildir ve yatırım kararlarınızdan model geliştiricisi sorumlu tutulamaz.
- Downloads last month
- 201
4-bit
5-bit
6-bit
8-bit
16-bit
Model tree for emircansevdi/Mihenk-LLM-v2-35B-A3B-Turkish-Financial-Model-GGUF
Base model
Qwen/Qwen3.6-35B-A3B