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https://github.com/meta-llama/llama-stack.git
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da9f0b7869
# What does this PR do? - Updates ImageContentItemImageURL import - fixes `embedding_dimensions` metadata param ## Test Plan - Ran pytest locally, verified embedding tests pass with new types  cc: @dglogo @sumitb
61 lines
1.9 KiB
Python
61 lines
1.9 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from llama_stack.apis.models import ModelType
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from llama_stack.models.llama.datatypes import CoreModelId
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from llama_stack.providers.utils.inference.model_registry import (
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ProviderModelEntry,
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build_hf_repo_model_entry,
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)
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_MODEL_ENTRIES = [
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build_hf_repo_model_entry(
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"meta/llama3-8b-instruct",
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CoreModelId.llama3_8b_instruct.value,
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),
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build_hf_repo_model_entry(
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"meta/llama3-70b-instruct",
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CoreModelId.llama3_70b_instruct.value,
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),
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build_hf_repo_model_entry(
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"meta/llama-3.1-8b-instruct",
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CoreModelId.llama3_1_8b_instruct.value,
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),
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build_hf_repo_model_entry(
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"meta/llama-3.1-70b-instruct",
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CoreModelId.llama3_1_70b_instruct.value,
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),
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build_hf_repo_model_entry(
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"meta/llama-3.1-405b-instruct",
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CoreModelId.llama3_1_405b_instruct.value,
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),
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build_hf_repo_model_entry(
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"meta/llama-3.2-1b-instruct",
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CoreModelId.llama3_2_1b_instruct.value,
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),
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build_hf_repo_model_entry(
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"meta/llama-3.2-3b-instruct",
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CoreModelId.llama3_2_3b_instruct.value,
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),
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build_hf_repo_model_entry(
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"meta/llama-3.2-11b-vision-instruct",
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CoreModelId.llama3_2_11b_vision_instruct.value,
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),
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build_hf_repo_model_entry(
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"meta/llama-3.2-90b-vision-instruct",
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CoreModelId.llama3_2_90b_vision_instruct.value,
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),
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ProviderModelEntry(
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provider_model_id="baai/bge-m3",
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model_type=ModelType.embedding,
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metadata={
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"embedding_dimension": 1024,
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"context_length": 8192,
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},
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),
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# TODO(mf): how do we handle Nemotron models?
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# "Llama3.1-Nemotron-51B-Instruct" -> "meta/llama-3.1-nemotron-51b-instruct",
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]
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