mirror of
https://github.com/meta-llama/llama-stack.git
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86 lines
2.1 KiB
YAML
86 lines
2.1 KiB
YAML
version: '2'
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image_name: meta-reference-gpu
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docker_image: null
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conda_env: meta-reference-gpu
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apis:
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- agents
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- inference
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- memory
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- safety
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- telemetry
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- datasetio
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- post_training
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providers:
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inference:
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- provider_id: meta-reference-inference
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provider_type: inline::meta-reference
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config:
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model: ${env.INFERENCE_MODEL}
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max_seq_len: 4096
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checkpoint_dir: ${env.INFERENCE_CHECKPOINT_DIR:null}
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datasetio:
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- provider_id: huggingface-0
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provider_type: remote::huggingface
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config: {}
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memory:
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- provider_id: faiss
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provider_type: inline::faiss
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config:
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kvstore:
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type: sqlite
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namespace: null
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db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/meta-reference-gpu}/faiss_store.db
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safety:
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- provider_id: llama-guard
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provider_type: inline::llama-guard
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config: {}
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agents:
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- provider_id: meta-reference
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provider_type: inline::meta-reference
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config:
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persistence_store:
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type: sqlite
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namespace: null
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db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/meta-reference-gpu}/agents_store.db
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telemetry:
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- provider_id: meta-reference
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provider_type: inline::meta-reference
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config: {}
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post_training:
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- provider_id: meta-reference-post-training
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provider_type: inline::meta-reference
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config:
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model: ${env.INFERENCE_MODEL}
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checkpoint_dir: ${env.INFERENCE_CHECKPOINT_DIR:null}
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metadata_store:
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namespace: null
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type: sqlite
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db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/meta-reference-gpu}/registry.db
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models:
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- metadata: {}
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model_id: ${env.INFERENCE_MODEL}
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provider_id: meta-reference-inference
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provider_model_id: null
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shields: []
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memory_banks: []
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datasets:
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- dataset_id: alpaca
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provider_id: huggingface-0
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url:
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uri: https://huggingface.co/datasets/tatsu-lab/alpaca
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metadata:
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path: tatsu-lab/alpaca
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name:
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split: train
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dataset_schema:
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instruction:
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type: string
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input:
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type: string
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output:
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type: string
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text:
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type: string
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scoring_fns: []
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eval_tasks: []
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