Text Generation
GGUF
quantized
quantization
apex
apex-quant
custom-quantization
unsloth-studio
Mixture of Experts
reasoning
llama.cpp
qwen35moe
conversational
imatrix
Instructions to use IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-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 IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-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 IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-GGUF:Q4_0 # Run inference directly in the terminal: llama cli -hf IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-GGUF:Q4_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-GGUF:Q4_0 # Run inference directly in the terminal: llama cli -hf IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-GGUF:Q4_0
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 IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-GGUF:Q4_0 # Run inference directly in the terminal: ./llama-cli -hf IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-GGUF:Q4_0
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 IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-GGUF:Q4_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-GGUF:Q4_0
Use Docker
docker model run hf.co/IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-GGUF:Q4_0
- Llama new
- LM Studio
- Jan
- vLLM
How to use IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-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": "IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-GGUF:Q4_0
- Ollama
How to use IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-GGUF with Ollama:
ollama run hf.co/IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-GGUF:Q4_0
- Unsloth Desktop
- Pi
How to use IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-GGUF:Q4_0
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": "IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-GGUF:Q4_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-GGUF with Docker Model Runner:
docker model run hf.co/IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-GGUF:Q4_0
- Lemonade
How to use IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-GGUF:Q4_0
Run and chat with the model
lemonade run user.KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-GGUF-Q4_0
List all available models
lemonade list
- Hermes Agent
How to use IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-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 IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-GGUF:Q4_0
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 IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-GGUF:Q4_0
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-GGUF:Q4_0
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 "IsValorum/KAT-Coder-V2.5-Dev-APEX-I-MiniPlus-V2.1-GGUF:Q4_0" \ --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"
Commit History
2 days ago
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Repair dead collection links
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16 days ago
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Add companion mtp-KAT-Coder-V2.5-Dev-Q4_0.gguf draft model for speculative decoding
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17 days ago
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Update README: Standardize independent compute and student support notice
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18 days ago
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Update 27B cross-links to canonical public V3 editions
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19 days ago
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Add Swift-1.5 to 27B VAL-APEX-I recommended editions
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20 days ago
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Add official Ko-fi community compute fund and priority model requests
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Fix: Remove extraneous duplicate endif tag in chat_template.jinja
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Promote Qwen3.8 27B V3 editions with explicit WikiText-2 PPL improvements
Verified signatureAdd MiniPlus V3 and NanoPlus V3 links and parenthesized PPL comparisons with GSQ-RCO IQ3_S in the existing note. Remove the word Base from the promotional names and note text, preserving technical content outside the notes.2cb713b
21 days ago
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Fix: Align tool_calls syntax with standard Qwen JSON format for llama.cpp parser compatibility
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Feature VAL-APEX-I 27B editions and organize model recommendation links
Verified signatureDocumentation-only update to recommendation blocks; measurements and quantization recipes unchanged.b0ee453
25 days ago
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Harden agentic tool execution, strict registry constraints, and thinking pruning
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26 days ago
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Fix audited tensor quantization map
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27 days ago
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Update chat_template.jinja with official KAT-Coder Kwaipilot official native format and normalized escapes
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28 days ago
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docs: add hardened agentic chat template section to TOC and specifications
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feat(chat_template): add hardened agentic chat template with tool-call safeguards and multi-turn preservation
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docs: add critical coding syntax & repeat penalty advisory to TOC and specs
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Show direct Ko-fi URL
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Number navigation and refine optional support
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Complete navigation index and remove duplicate support block
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Move navigation to top and clarify optional support
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Add optional Ko-fi support link
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Correct fidelity tiers against measured delta perplexity
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Add compact model-specific V2.1 comparison table
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Add Qwen3.6 Abliterated V2.1 to lineup links
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Replace generic Q5-Q6 redundancy with exact verified quality tier
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Identify MiniPlus V2.1 edition in lineup links
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Clarify established 35B MoE lineup and cross-links
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Expand V2.1 model cross-promotion
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Promote established V2.1 APEX-I-MiniPlus releases
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Add system RAM inference guidance
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Restore independent benchmark references; neutralize quantizer attribution
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Remove third-party user references from model card
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Keep WikiText-2 results while removing evaluation parameters
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Remove exact RAM-offload and laptop throughput figures
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Fix nested emphasis in Q5-Q6 fidelity statement
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Emphasize Q5-Q6 fidelity at lower-than-Q3_K_M weight
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Update model-specific Q3_K_M size reference (16.2 GB)
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Tie Q5-Q6 fidelity callout to model result
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Make quality comparison model-specific
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Clarify external benchmark attribution
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Separate author sampling recommendation from zephel01 llmbench setting & explicit Occamy V2 references
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Replace model-specific Occamy failure example with generic checkpoint fidelity notice
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Update model-specific Delta PPL and baseline perplexity values
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Add third-party benchmark (zephel01), sampling parameters, and VRAM scaling
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Add third-party benchmark (zephel01), sampling parameters, and VRAM scaling
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Add third-party benchmark (zephel01), sampling parameters, and VRAM scaling
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Add third-party benchmark (zephel01), sampling parameters, and VRAM scaling
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Add third-party benchmark (zephel01), sampling parameters, and VRAM scaling
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Add Quality Spectrum table comparing APEX-I-MiniPlus V2.1 against standard flat quantizations
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Eliminate unintentional strikethrough by replacing bare tildes with explicit approx.
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