Comments (2)
Tried the "N_GQA: '8'" from another open issue, the container loads now, but the speed is 1 token per 1 minute or so.
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Thanks for reporting, @itamargero. We have added N_GQA: 8
in the docker-compose.yml for the 70B model. The token generation is slow on M1 due to lack of GPU offloading and Metal support, so currently only the CPU is being utilized. We hope to add Metal support soon. Closing this issue for now.
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Related Issues (20)
- Unable to build CUDA-enabled image, missing Makefile HOT 17
- Running does not work on MacOS with homebrew conda HOT 3
- nvidia-container-cli error HOT 2
- Fresh Install - API Never Starts HOT 1
- Infinite loop "No such file run.sh"
- Are there any plans for load custom models? HOT 1
- airgapped npm issues in ui container
- Only works with cuda the 7b model
- Brackets in run.sh
- Installation on windows - please elaborate more
- docker compose: Permission denied running /api/run.sh HOT 2
- CUDA Support for Kubernetes
- Errors thrown when trying to start llama-gpt api using docker-compose-gguf.yml HOT 2
- IPv6 support HOT 1
- Not enough space HOT 1
- Support Multi-part .bin files?
- Is there the ability to swap the language to answer?
- Llama GPT extremely slow on Umbrel Home HOT 1
- Can't use GPU: could not select device driver "nvidia" with capabilities: [[gpu]] HOT 3
- Can't run on Linux HOT 1
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