forked from phoenix-oss/llama-stack-mirror
1.9 KiB
1.9 KiB
Cerebras Distribution
The llamastack/distribution-cerebras distribution consists of the following provider configurations.
| API | Provider(s) |
|---|---|
| agents | inline::meta-reference |
| datasetio | remote::huggingface, inline::localfs |
| eval | inline::meta-reference |
| inference | remote::cerebras |
| safety | inline::llama-guard |
| scoring | inline::basic, inline::llm-as-judge, inline::braintrust |
| telemetry | inline::meta-reference |
| tool_runtime | remote::brave-search, remote::tavily-search, inline::code-interpreter, inline::rag-runtime |
| vector_io | inline::faiss, remote::chromadb, remote::pgvector |
Environment Variables
The following environment variables can be configured:
LLAMA_STACK_PORT: Port for the Llama Stack distribution server (default:5001)CEREBRAS_API_KEY: Cerebras API Key (default: ``)
Models
The following models are available by default:
meta-llama/Llama-3.1-8B-Instruct (llama3.1-8b)meta-llama/Llama-3.3-70B-Instruct (llama-3.3-70b)
Prerequisite: API Keys
Make sure you have access to a Cerebras API Key. You can get one by visiting cloud.cerebras.ai.
Running Llama Stack with Cerebras
You can do this via Conda (build code) or Docker which has a pre-built image.
Via Docker
This method allows you to get started quickly without having to build the distribution code.
LLAMA_STACK_PORT=5001
docker run \
-it \
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-v ./run.yaml:/root/my-run.yaml \
llamastack/distribution-cerebras \
--yaml-config /root/my-run.yaml \
--port $LLAMA_STACK_PORT \
--env CEREBRAS_API_KEY=$CEREBRAS_API_KEY
Via Conda
llama stack build --template cerebras --image-type conda
llama stack run ./run.yaml \
--port 5001 \
--env CEREBRAS_API_KEY=$CEREBRAS_API_KEY