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bump ollama/ollama to v0.18.0 #1

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bump ollama/ollama to v0.18.0 #1

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12 changes: 4 additions & 8 deletions dappnode_package.json
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@
"upstream": [
{
"repo": "ollama/ollama",
"version": "v0.17.7",
"version": "v0.18.0",
"arg": "OLLAMA_VERSION"
}
],
Expand All @@ -14,13 +14,9 @@
"type": "service",
"author": "DAppNode Association <admin@dappnode.io> (https://github.com/dappnode)",
"license": "GPL-3.0",
"categories": [
"AI"
],
"categories": ["AI"],
"links": {
"Models library": "https://ollama.com/library"
},
"architectures": [
"linux/amd64"
]
}
"architectures": ["linux/amd64"]
}
2 changes: 1 addition & 1 deletion docker-compose.yml
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Expand Up @@ -4,7 +4,7 @@ services:
build:
context: ollama
args:
OLLAMA_VERSION: v0.17.7
OLLAMA_VERSION: v0.18.0
container_name: ollama.ollama.dnp.dappnode.eth
volumes:
- ollama:/root/.ollama
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7 changes: 2 additions & 5 deletions package_variants/cpu/dappnode_package.json
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Expand Up @@ -5,9 +5,6 @@
"Model Manager": "http://ui.ollama-cpu.dappnode",
"api": "http://ollama-cpu.dappnode:11434"
},
"architectures": [
"linux/amd64",
"linux/arm64"
],
"architectures": ["linux/amd64", "linux/arm64"],
"description": "Run large language models locally on your DAppNode. Ollama inference engine with CPU-only support.\n\n**Features:**\n- CPU acceleration for inference\n- Complete privacy - all processing stays local\n- Support for multiple LLM models (Llama, Mistral, CodeLlama, etc.)\n\n**Requirements:**\n- At least 8GB RAM (16GB+ recommended)\n- Sufficient storage for models (10GB+ recommended)\n"
}
}
7 changes: 2 additions & 5 deletions package_variants/nvidia/dappnode_package.json
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Expand Up @@ -5,9 +5,6 @@
"Model Manager": "http://ui.ollama-nvidia.dappnode",
"api": "http://ollama-nvidia.dappnode:11434"
},
"architectures": [
"linux/amd64",
"linux/arm64"
],
"architectures": ["linux/amd64", "linux/arm64"],
"description": "Run large language models locally on your DAppNode with GPU acceleration. Ollama with NVIDIA GPU support for GPU inference.\n\n**Features:**\n- NVIDIA GPU acceleration\n- Complete privacy - all processing stays local\n- Support for multiple LLM models (Llama, Mistral, CodeLlama, etc.)\n\n**Requirements:**\n- NVIDIA GPU with CUDA support\n- At least 8GB RAM (16GB+ recommended)\n- Sufficient storage for models (10GB+ recommended)\n"
}
}