AutoConfig.from_pretrained:从path/config.json中加载模型配置信息 更新模型配置信息:model = Model(config) PreTrainedModel.from_pretrained:加载模型结构和模型参数 load_checkpoint 从checkpoint 中加载模型 parameter,而不加载模型结构
from_pretrained(name) trainer.model.to(training_args.device) return experiment, trainer def load_gpt_fewshot_baseline_trainer( dataset_name: str = "one_million_instructions", 2 changes: 0 additions & 2 deletions 2 vec2text/models/inversion.py Original file line numberDiff line numberDiff ...
I have not used "load_from." After looking through the code, I can't seem to find a place where the value of "pretrained" is actually used to load weights, so I suspect I may actually have been training from scratch each time. Do I need to use "load_from" in order to fine tune...
tokenizer = BertTokenizer.from_pretrained(pretrained)model = AlbertForMaskedLM.from_pretrained(pretrained)# 它包装在PyTorch DistributedDataParallel或DataParallel中model_to_save = model.module if hasattr(model, 'module') else modeltorch.save(model_to_save.state_dict(), 'pytorch_model_unzip.bin', _...
根据你提供的信息,我将详细解释如何导入llava.model.builder模块并从该模块中调用load_pretrained_model函数。 1. 导入llava.model.builder模块 在Python中,要导入一个模块,可以使用import语句。对于llava.model.builder模块,你可以使用以下代码导入它: python import llava.model.builder 这样,你就导入了llava.model...
>>> from transformers import AutoTokenizer >>> tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased") >>> def encode(batch): ... return tokenizer(batch["sentence1"], padding="longest", truncation=True, max_length=512, return_tensors="pt") >>> dataset.set_transform(encode) >>>...
test_cfg, pretrained, init_cfg) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 我们可以发现RetinaNet类构造函数的参数刚好和配置文件中type='RetinaNet'的字典的其他键值对应。所以build_detector()函数的作用就是根据dict中的type找到对应的类,然后使用dict中传入的参数来对类进行初始...
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if pretrained: state_dict = load_state_dict_from_url("https://download.pytorch.org/models/vgg16-397923af.pth", model_dir="./model_data") state_dict = {k.replace('features.', '') : v for k, v in state_dict.items()} # 如果字典中存在'features.',就替换为'' model.load_state_di...
In configurations for dataset we have 'pretrained', in default_runtime.py we have 'load_from'. I wonder what is the difference between them.Collaborator hhaAndroid commented Apr 6, 2021 pretrained is generally used to load backbone weights, but load_from is used to load the entire model ...