Instructions to use patdev/k3-a40-bootstrap 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 patdev/k3-a40-bootstrap 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 patdev/k3-a40-bootstrap:BF16 # Run inference directly in the terminal: llama cli -hf patdev/k3-a40-bootstrap:BF16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf patdev/k3-a40-bootstrap:BF16 # Run inference directly in the terminal: llama cli -hf patdev/k3-a40-bootstrap:BF16
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 patdev/k3-a40-bootstrap:BF16 # Run inference directly in the terminal: ./llama-cli -hf patdev/k3-a40-bootstrap:BF16
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 patdev/k3-a40-bootstrap:BF16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf patdev/k3-a40-bootstrap:BF16
Use Docker
docker model run hf.co/patdev/k3-a40-bootstrap:BF16
- LM Studio
- Jan
- Ollama
How to use patdev/k3-a40-bootstrap with Ollama:
ollama run hf.co/patdev/k3-a40-bootstrap:BF16
- Unsloth Desktop
- Docker Model Runner
How to use patdev/k3-a40-bootstrap with Docker Model Runner:
docker model run hf.co/patdev/k3-a40-bootstrap:BF16
- Lemonade
How to use patdev/k3-a40-bootstrap with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull patdev/k3-a40-bootstrap:BF16
Run and chat with the model
lemonade run user.k3-a40-bootstrap-BF16
List all available models
lemonade list
- Atomic Chat
chien: images 4 + KV 14,5 GiB, identique au bootstrap
Browse files
chien.py
CHANGED
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@@ -44,7 +44,7 @@ MOTEUR_CMD = [
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"--served-model-name", "flashnext", "--host", "127.0.0.1", "--port", "8000",
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"--max-model-len", "262144", "--max-num-seqs", "16",
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"--gpu-memory-utilization", "0.93",
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"--kv-cache-memory-bytes", "
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"--distributed-executor-backend", "mp",
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"--reasoning-parser", "qwen3", "--tool-call-parser", "qwen3_coder",
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# Le plafond a 0 rendait un 400 sur toute capture collee dans Claude Code
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"--served-model-name", "flashnext", "--host", "127.0.0.1", "--port", "8000",
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"--max-model-len", "262144", "--max-num-seqs", "16",
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"--gpu-memory-utilization", "0.93",
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+
"--kv-cache-memory-bytes", "15569256448", # 14,5 GiB : marge pour l'encodeur d'images
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"--distributed-executor-backend", "mp",
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"--reasoning-parser", "qwen3", "--tool-call-parser", "qwen3_coder",
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# Le plafond a 0 rendait un 400 sur toute capture collee dans Claude Code
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