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[ColossalEval] support for vllm (#6056)
* support vllm * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * modify vllm and update readme * run pre-commit * remove dupilicated lines and refine code * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * update param name * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * refine code * update readme * refine code * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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@@ -72,7 +72,7 @@ default_inference_kwargs = {
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"calculate_loss": True,
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"all_classes": None,
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"language": "English",
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"pretrain": False,
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"calculate_overall_loss": False,
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"max_new_tokens": 256,
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}
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@@ -114,7 +114,7 @@ class GSMDataset(BaseDataset):
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dataset[split][subject]["inference_kwargs"] = copy.deepcopy(default_inference_kwargs)
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if forward_only:
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dataset[split][subject]["inference_kwargs"]["pretrain"] = True
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dataset[split][subject]["inference_kwargs"]["calculate_overall_loss"] = True
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if split == "test" and few_shot:
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dataset[split][subject]["inference_kwargs"]["few_shot_data"] = get_few_shot_data()
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