use llama 3.1 in tests
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@@ -32,7 +32,7 @@ jobs:
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name: Run tests
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command: |
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source env/bin/activate
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ls ~/.cache/huggingface/hub/models--mlx-community--Meta-Llama-3-8B-Instruct-4bit/**/* || true
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ls ~/.cache/huggingface/hub/models--mlx-community--Meta-Llama-3.1-8B-Instruct-4bit/**/* || true
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METAL_XCODE=1 python3 -m exo.inference.test_inference_engine
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- save_cache:
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paths:
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@@ -112,7 +112,7 @@ jobs:
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command: |
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source env/bin/activate
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# Check if cached files are present
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ls ~/.cache/huggingface/hub/models--mlx-community--Meta-Llama-3-8B-Instruct-4bit/**/* || true
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ls ~/.cache/huggingface/hub/models--mlx-community--Meta-Llama-3.1-8B-Instruct-4bit/**/* || true
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# Start first instance
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DEBUG_DISCOVERY=9 DEBUG=9 python3 main.py --inference-engine mlx --node-id "node1" --listen-port 5678 --broadcast-port 5679 --chatgpt-api-port 8000 --chatgpt-api-response-timeout-secs 900 > output1.log 2>&1 &
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@@ -146,7 +146,7 @@ jobs:
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curl -s http://localhost:8000/v1/chat/completions \
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-H "Content-Type: application/json" \
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-d '{
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"model": "llama-3-8b",
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"model": "llama-3.1-8b",
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"messages": [{"role": "user", "content": "Keep responses concise. Placeholder to load model..."}],
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"temperature": 0.7
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}'
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@@ -157,7 +157,7 @@ jobs:
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response_1=$(curl -s http://localhost:8000/v1/chat/completions \
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-H "Content-Type: application/json" \
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-d '{
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"model": "llama-3-8b",
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"model": "llama-3.1-8b",
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"messages": [{"role": "user", "content": "Keep responses concise. Who was the king of pop?"}],
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"temperature": 0.7
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}')
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@@ -169,7 +169,7 @@ jobs:
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response_2=$(curl -s http://localhost:8000/v1/chat/completions \
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-H "Content-Type: application/json" \
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-d '{
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"model": "llama-3-8b",
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"model": "llama-3.1-8b",
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"messages": [{"role": "user", "content": "Keep responses concise. Who was the king of pop?"}],
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"temperature": 0.7
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}')
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