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d362d2d740
This PR adds the ability to generate embeddings in all supported inference providers. ``` pytest -v -s llama_stack/providers/tests/inference/test_embeddings.py -k "bedrock" --inference-model="amazon.titan-embed-text-v2:0" --env EMBEDDING_DIMENSION=1024 pytest -v -s -k "vllm" --inferrence-model="intfloat/e5-mistral-7b-instruct" llama_stack/providers/tests/inference/test_embeddings.py --env EMBEDDING_DIMENSION=4096 --env VLLM_URL="http://localhost:9798/v1" pytest -v -s --inference-model="nomic-ai/nomic-embed-text-v1.5" llama_stack/providers/tests/inference/test_embeddings.py -k "fireworks" --env FIREWORKS_API_KEY=<API_KEY>--env EMBEDDING_DIMENSION=128 pytest -v -s --inference-model="togethercomputer/m2-bert-80M-2k-retrieval" llama_stack/providers/tests/inference/test_embeddings.py -k "together" --env TOGETHER_API_KEY=<API_KEY>--env EMBEDDING_DIMENSION=768 pytest -v -s -k "ollama" --inference-model="all-minilm:v8" llama_stack/providers/tests/inference/test_embeddings.py --env EMBEDDING_DIMENSION=384 torchrun $CONDA_PREFIX/bin/pytest -v -s -k "meta_reference" --inference-model="sentence-transformers/all-MiniLM-L6-v2" llama_stack/providers/tests/inference/test_embeddings.py --env EMBEDDING_DIMENSION=384 ``` |
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| .. | ||
| agents | ||
| batch_inference | ||
| common | ||
| datasetio | ||
| datasets | ||
| eval | ||
| eval_tasks | ||
| inference | ||
| inspect | ||
| memory | ||
| memory_banks | ||
| models | ||
| post_training | ||
| safety | ||
| scoring | ||
| scoring_functions | ||
| shields | ||
| synthetic_data_generation | ||
| telemetry | ||
| __init__.py | ||
| resource.py | ||
| version.py | ||