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https://github.com/meta-llama/llama-stack.git
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57 lines
1.8 KiB
Python
57 lines
1.8 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 typing import Optional
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from llama_models.datatypes import ModelFamily
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from llama_models.schema_utils import json_schema_type
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from llama_models.sku_list import all_registered_models, resolve_model
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from pydantic import BaseModel, Field, field_validator
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from llama_toolchain.inference.api import QuantizationConfig
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@json_schema_type
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class MetaReferenceImplConfig(BaseModel):
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model: str = Field(
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default="Meta-Llama3.1-8B-Instruct",
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description="Model descriptor from `llama model list`",
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)
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quantization: Optional[QuantizationConfig] = None
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torch_seed: Optional[int] = None
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max_seq_len: int
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max_batch_size: int = 1
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@field_validator("model")
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@classmethod
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def validate_model(cls, model: str) -> str:
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permitted_models = [
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m.descriptor()
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for m in all_registered_models()
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if m.model_family == ModelFamily.llama3_1
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]
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if model not in permitted_models:
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model_list = "\n\t".join(permitted_models)
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raise ValueError(
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f"Unknown model: `{model}`. Choose from [\n\t{model_list}\n]"
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)
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return model
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@property
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def model_parallel_size(self) -> int:
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# HUGE HACK ALERT: this will be fixed when we move inference configuration
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# to ModelsRegistry and we can explicitly ask for `model_parallel_size`
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# as configuration there
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gpu_count = 1
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resolved = resolve_model(self.model)
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assert resolved is not None
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descriptor = resolved.descriptor().lower()
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if "-70b" in descriptor or "-405b" in descriptor:
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gpu_count = 8
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return gpu_count
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