Instructions to use spytak/panora-model-12k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use spytak/panora-model-12k with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="spytak/panora-model-12k", filename="qwen3-14b.Q4_K_M.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use spytak/panora-model-12k 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 spytak/panora-model-12k:Q4_K_M # Run inference directly in the terminal: llama cli -hf spytak/panora-model-12k:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf spytak/panora-model-12k:Q4_K_M # Run inference directly in the terminal: llama cli -hf spytak/panora-model-12k: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 spytak/panora-model-12k:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf spytak/panora-model-12k: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 spytak/panora-model-12k:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf spytak/panora-model-12k:Q4_K_M
Use Docker
docker model run hf.co/spytak/panora-model-12k:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use spytak/panora-model-12k with Ollama:
ollama run hf.co/spytak/panora-model-12k:Q4_K_M
- Unsloth Studio
How to use spytak/panora-model-12k 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 spytak/panora-model-12k 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 spytak/panora-model-12k to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for spytak/panora-model-12k to start chatting
- Pi
How to use spytak/panora-model-12k with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf spytak/panora-model-12k: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": "spytak/panora-model-12k:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use spytak/panora-model-12k with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf spytak/panora-model-12k: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 spytak/panora-model-12k:Q4_K_M
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use spytak/panora-model-12k with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf spytak/panora-model-12k: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 "spytak/panora-model-12k: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 spytak/panora-model-12k with Docker Model Runner:
docker model run hf.co/spytak/panora-model-12k:Q4_K_M
- Lemonade
How to use spytak/panora-model-12k with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull spytak/panora-model-12k:Q4_K_M
Run and chat with the model
lemonade run user.panora-model-12k-Q4_K_M
List all available models
lemonade list
| FROM qwen3-14b.Q4_K_M.gguf | |
| TEMPLATE """{{- if .Messages }} | |
| {{- if or .System .Tools }}<|im_start|>system | |
| {{- if .System }} | |
| {{ .System }} | |
| {{- end }} | |
| {{- if .Tools }} | |
| # Tools | |
| You may call one or more functions to assist with the user query. | |
| You are provided with function signatures within <tools></tools> XML tags: | |
| <tools> | |
| {{- range .Tools }} | |
| {"type": "function", "function": {{ .Function }}} | |
| {{- end }} | |
| </tools> | |
| For each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags: | |
| <tool_call> | |
| {"name": <function-name>, "arguments": <args-json-object>} | |
| </tool_call> | |
| {{- end }}<|im_end|> | |
| {{ end }} | |
| {{- range $i, $_ := .Messages }} | |
| {{- $last := eq (len (slice $.Messages $i)) 1 -}} | |
| {{- if eq .Role "user" }}<|im_start|>user | |
| {{ .Content }}<|im_end|> | |
| {{ else if eq .Role "assistant" }}<|im_start|>assistant | |
| {{ if .Content }}{{ .Content }} | |
| {{- else if .ToolCalls }}<tool_call> | |
| {{ range .ToolCalls }}{"name": "{{ .Function.Name }}", "arguments": {{ .Function.Arguments }}} | |
| {{ end }}</tool_call> | |
| {{- end }}{{ if not $last }}<|im_end|> | |
| {{ end }} | |
| {{- else if eq .Role "tool" }}<|im_start|>user | |
| <tool_response> | |
| {{ .Content }} | |
| </tool_response><|im_end|> | |
| {{ end }} | |
| {{- if and (ne .Role "assistant") $last }}<|im_start|>assistant | |
| {{ end }} | |
| {{- end }} | |
| {{- else }} | |
| {{- if .System }}<|im_start|>system | |
| {{ .System }}<|im_end|> | |
| {{ end }}{{ if .Prompt }}<|im_start|>user | |
| {{ .Prompt }}<|im_end|> | |
| {{ end }}<|im_start|>assistant | |
| {{ end }}{{ .Response }}{{ if .Response }}<|im_end|>{{ end }}""" | |
| SYSTEM """Sen Panora, empatik ve destekleyici bir Türkçe ruh sağlığı asistanısın. | |
| KİŞİLİK & TON: | |
| - Vakur, ağırbaşlı ve empatik ol | |
| - Validation ve mirroring teknikleri kullan | |
| - Açık uçlu takip soruları sor | |
| - Casual dil KULLANMA (kanka, canım, hallederiz gibi kelimeler yasak) | |
| DÜŞÜNME SÜRECİ: | |
| - Karmaşık durumlarda | |
| <div class="think">tagları içinde düşün<br />- Kullanıcının duygusal durumunu analiz et<br />- Empati ve metodoloji dengesini kur<br />- Thinking sonrası kullanıcıya sadece cevabı göster<br /><br />KRİZ YÖNLENDORME (EĞİTİMİNDE ÖĞRENDİN):<br />- İntihar/kendine zarar düşünceleri → 112 veya ALO 183'e yönlendir<br />- Şiddet/taciz/istismar durumları → ALO 183 (0549 417 2605)<br />- Madde bağımlılığı → ALO 191<br />- 182 numarasını ASLA KULLANMA<br /><br />ÖNEMLİ:<br />- Red flag durumlarını eğitiminde öğrendin, güven kendine<br />- Her cevap thinking gerektirmez, duruma göre karar ver<br />- Kullanıcı güvenliği her şeyden önemli<br /><br />Türkçe konuş."""<br /><br />PARAMETER stop "<|im_end|>"<br />PARAMETER stop "<|im_start|>"<br />PARAMETER stop "</div> | |
| " | |
| PARAMETER temperature 0.85 | |
| PARAMETER top_p 0.95 | |
| PARAMETER top_k 40 | |
| PARAMETER repeat_penalty 1.1 | |
| PARAMETER num_ctx 4096 | |
| PARAMETER num_predict 300 |