36 lines
1.3 KiB
Python
36 lines
1.3 KiB
Python
#
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# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
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# Copyright 2023 The vLLM team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# This file is a part of the vllm-ascend project.
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#
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from modelscope import snapshot_download # type: ignore[import-untyped]
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from tests.e2e.conftest import VllmRunner
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def test_quant_W8A8():
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max_tokens = 5
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example_prompts = [
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"vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs."
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]
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with VllmRunner(
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snapshot_download("vllm-ascend/Qwen2.5-0.5B-Instruct-W8A8"),
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max_model_len=8192,
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enforce_eager=True,
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gpu_memory_utilization=0.7,
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quantization="ascend",
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) as vllm_model:
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vllm_model.generate_greedy(example_prompts, max_tokens)
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