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This looks like a great project. Given the costs, I imagine many might want to run on dedicated hardware with GPU - yet: > GPT4All: When you run locally, RAGst
by e12e 3y ago
This looks like a great project. Given the costs, I imagine many might want to run on dedicated hardware with GPU - yet:
> GPT4All: When you run locally, RAGstack will download and deploy Nomic AI's gpt4all model, which runs on consumer CPUs.
> Falcon-7b: On the cloud, RAGstack deploys Technology Innovation Institute's falcon-7b model onto a GPU-enabled GKE cluster.
> LLama 2: On the cloud, RAGstack can also deploy the 7B paramter version of Meta's Llama 2 model onto a GPU-enabled GKE cluster.
Why not llama2 on dedicated/local hardware? Memory and download size requirements?
Ed: After reading the linked tutorial - it looks like the built docker container will run fine on local/dedicated hardware?
https://www.psychic.dev/post/how-to-deploy-llama-2-to-google-cloud-gcp https://www.psychic.dev/post/how-to-deploy-llama-2-to-google...
- jasonwcfan 3y agoYep the docker containers should run fine on local hardware, but the terraform config only supports GCP right now. In terms of cost - just ran our deployed cluster through GCP's pricing calculator and it's about $300 USD per month. Definitely not cheap for individual use, but pretty affordable for enterprise use. Running the 40B parameter version will be significantly more.