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Click to add a brief description of the dataset (Markdown and LaTeX enabled). Provide: a high-level explanation of the dataset characteristics explain motivations and summary of its content potential use cases of the dataset
step 2. 准备data 和 trainer 并进行训练 data = load_dataset(data_path) trainer = transformers.Trainer( model=model, train_dataset=train_data, eval_dataset=val_data, args=transformers.TrainingArguments( per_device_train_batch_size=micro_batch_size, gradient_accumulation_steps=gradient_accumulation_st...
import transformers from datasets import load_dataset from peft import LoraConfig, get_peft_model, get_peft_model_state_dict, prepare_model_for_int8_training, set_peft_model_state_dict, from transformers import LlamaForCausalLM, LlamaTokenizer model = LlamaForCausalLM.from_pretrained(base_model, ...
If None, we use the same model as the one we are -e, --evaluation_dataset=EVALUATION_DATASET Type: Union Defaul... Path to the evaluation dataset or a function that returns a dataframe. If None, we use the default evaluat ion -a, --annotators_config=ANNOTATORS_CONFIG Type: Union ...
eval_set = datasets.load_dataset("tatsu-lab/alpaca_eval","alpaca_eval")["eval"] forexampleineval_set: # generate here is a placeholder for your models generations example["output"] = generate(example["instruction"]) 2)计算 golden 输出 reference_outputs。默认情况下,在 AlpacaEval 上使用 text...
eval_set = datasets.load_dataset("tatsu-lab/alpaca_eval","alpaca_eval")["eval"] forexampleineval_set: # generate here is a placeholder for your models generations example["output"] = generate(example["instruction"]) 2)计算 golden 输出 reference_outputs。默认情况下,在 AlpacaEval 上使用 text...
Trainer( model=model, train_dataset=train_data, eval_dataset=val_data, args=transformers.TrainingArguments( ... This is pretty simple. At the end, the script produces a model folder with checkpoints, adapter weights, and adapter configuration. Next, let's look at the main flow of generate...
alpaca-chinese-dataset 失夜**ma上传2.67 MB文件格式zipalpacachatglmllm alpaca中文指令微调数据集 (0)踩踩(0) 所需:1积分 CallRecored 2025-02-24 20:54:55 积分:1 facebook 2025-02-24 20:54:21 积分:1 dpl-data-testserver 2025-02-24 20:45:45...
AlpacaEval dataset: a simplification of AlpacaFarm's evaluation set, where "instructions" and " inputs" are merged into one field, and reference outputs are longer. Details here.When to use AlpacaEval? Our automatic evaluator is a quick and cheap proxy for human evaluation of simple instruction...