model_type = "bert" def __init__( self, vocab_size=30522, hidden_size=768, num_hidden_layers=12,num_attention_heads=12, intermediate_size=3072, hidden_act="gelu", hidden_dropout_prob=0.1, attention_probs_dropout_prob=0.1, max_position_embeddings=512, type_vocab_size=2, initializer_ran...
- This IS NOT expected if you are initializing BertModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model). <class 'transformers.models.bert.modeling_bert.BertModel'> 可以看到,。这一...
此处一样使用将model_name_or_path参数改为文件夹的路径即可。 python run_generation.py \ --model_type=gpt2 \ --model_name_or_path=/dfsdata2/yucc1_data/models/huggingface/gpt2 掌握了以上方法后,transformers库、文档里的其他样例都是一样的操作,无非是换个路径及模型。 4. 我下载好的一些预训练模...
set_trace() --> 120 return MODEL_TYPE_TO_PEFT_MODEL_MAPPING[peft_config.task_type](model, peft_config) 121 ipdb> peft_config PromptTuningConfig(peft_type=<PeftType.PROMPT_TUNING: 'PROMPT_TUNING'>, base_model_name_or_path='bigscience/bloomz-560m', task_type=<TaskType.CAUSAL_LM: '...
model_id='prajjwal1/bert-tiny'# note that we need to specify the numberofclassesforthistask # we can directly use themetadata(num_classes)storedinthe dataset model=AutoModelForSequenceClassification.from_pretrained(model_id,num_labels=train_dataset.features["label"].num_classes)tokenizer=AutoToke...
type_id=random.randint(0, 2), start_length=start_length ) if len(input_ids) + len(template_tokens) >= self.tokenizer.model_max_length - 2: break start = len(input_ids) input_ids.extend(template_tokens) end = len(input_ids)
总体是,将所需要的预训练模型、词典等文件下载至本地文件夹中 ,然后加载的时候model_name_or_path参数指向文件的路径即可。 2. 手动下载配置、词典、预训练模型等 首先打开网址:https://huggingface.co/models这个网址是huggingface/transformers支持的所有模型,目前大约一千多个。搜索gpt2(其他的模型类似,比如bert-ba...
model = transformers.BertModel.from_pretrained(MODEL_PATH,config = model_config) ### 利用分词器分词 利用分词器进行编码 * 对于单句:
"type": "InternalServerException", "message": "\nTapasModel requires the torch-scatter library but it was not found in your environment. You can install it with pip as\nexplained here: https://github.com/rusty1s/pytorch_scatter.\n" ...
(). I expected the model to save without error from either attempt. I have dug through the transformers source code, namely tokenization_utils_base.py and found that the 'add_special_tokens' attribute of the 'tokenizer_config' object is of type <class 'method'>. I don't kn...