T-Eval 现已加入 OpenCompass 评测平台,更多详细内容可参考以下链接! GitHub:https://github.com/open-compass/T-Eval OpenCompass官网:https://hub.opencompass.org.cn/dataset-detail/T-Eval 联系我们:opencompass@pjlab.org.cn 欢迎大家关注“司南评测体系”微信公众号,获取更多大模型评测相关知识~ 来源:https:...
transactional efficie transactional main bo transactional monetar transactiondatasettds transactionlogbackup transactions per page transactionswithfullc transaktionssystem transanal endoscop ic transarterial emboliz transasia airways transboundary transboundary crime transcatheter arteria transcaucasian sfsr transcend c...
(dataset, llm, args.out_dir, tmp_folder_name=tmp_folder_name, test_num=test_num) File "/home/ma-user/modelarts/user-job-dir/T-Eval/v0.2/test.py", line 74, in infer prediction = split_special_tokens(prediction) File "/home/ma-user/modelarts/user-job-dir/T-Eval/v0.2/test.py", ...
triangular ligament triangular load triangular mesh evalu triangular motion triangular oil groove triangular organizati triangular pelvis triangular phase plot triangular plug triangular root eleva triangular side ditch triangular spacing triangular stump triangular sword triangular tongue-and triangular velocity d...
sigmas = [] # For each row of the matrix (each point in our dataset) for i in range ( distances . shape [ 0 ]): # Make fn that returns perplexity of this row given sigma eval_fn = lambda sigma : \ perplexity ( distances [ i : i + 1 , :], np . array ( sigma )) ...
IDatasetManager IEvaluateMetricManager IMetricManager IMonitor InferenceException InferenceExceptionType IPerformanceMonitor ISweepable ISweepable<T> ITrainValidateDatasetManager ITrialRunner ITuner MLContextExtension MulticlassClassificationExperiment MulticlassClassificationMetric ...
File /local_disk0/.ephemeral_nfs/envs/pythonEnv-4d9998b4-a56e-4ea6-a7f3-02ddc4dade59/lib/python3.10/site-packages/transformers/trainer.py:405, in Trainer.__init__(self, model, args, data_collator, train_dataset, eval_dataset, tokenizer, model_init, compute_metrics, callbacks, optimizers...
def run_evaluation(chat_completion_fn, name, dataset_path): from azure.ai.generative.evaluate import evaluate path = pathlib.Path.cwd() / dataset_path dataset = load_jsonl(path) qna_fn = partial(copilot_qna, chat_completion_fn=chat_completion_fn) output_path = "./evaluation_output" clien...
UNKILLABLE Sorry the script already executed write commands against the dataset. UNKILLABLE The busy script was sent by a master instance in the context of replication and cannot be killed. NOTBUSY No scripts in execution right now. Lettuce客户端 ...
dataset), 100. * correct / len(train_loader.dataset))) @torch.no_grad() def evaluate(val_loader): global best_acc # 验证函数 val_loss = 0 correct = 0 for data, target in val_loader: data, target = data.to(device), target.to(device) output = net(data) # sum up batch loss ...