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atharvakalele/bhikari atharvakalele/bhikari Run large language models across several consumer machines over ordinary Ethernet. A model that fits in no single GPU you own can fit across all of them.
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Run large language models across several consumer machines over ordinary Ethernet. A model that fits in no single GPU you own can fit across all of them.
Shell
#consumer-hardware#distributed-inference#edge-ai#gpu#llama-cpp#llm#local-llm#pipeline-parallelism
help wanted open-problem
atharvakalele/bhikari atharvakalele/bhikari Run large language models across several consumer machines over ordinary Ethernet. A model that fits in no single GPU you own can fit across all of them.
Open project →
0
Run large language models across several consumer machines over ordinary Ethernet. A model that fits in no single GPU you own can fit across all of them.
Shell
#consumer-hardware#distributed-inference#edge-ai#gpu#llama-cpp#llm#local-llm#pipeline-parallelism
Add the ring hook to more model architectures 2 months ago
documentation help wanted good first issue
atharvakalele/bhikari atharvakalele/bhikari Run large language models across several consumer machines over ordinary Ethernet. A model that fits in no single GPU you own can fit across all of them.
Open project →
0
Run large language models across several consumer machines over ordinary Ethernet. A model that fits in no single GPU you own can fit across all of them.
Shell
#consumer-hardware#distributed-inference#edge-ai#gpu#llama-cpp#llm#local-llm#pipeline-parallelism
help wanted good first issue hardware-report
atharvakalele/bhikari atharvakalele/bhikari Run large language models across several consumer machines over ordinary Ethernet. A model that fits in no single GPU you own can fit across all of them.
Open project →
0
Run large language models across several consumer machines over ordinary Ethernet. A model that fits in no single GPU you own can fit across all of them.
Shell
#consumer-hardware#distributed-inference#edge-ai#gpu#llama-cpp#llm#local-llm#pipeline-parallelism