from transformers import pipeline tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-xxl") hf_model = T5ForConditionalGeneration.from_pretrained(hf_checkpoint_path) generator = pipeline("text2text-generation", model=hf_model, tokenizer=tokenizer) prompt = ( "mnli hypothesis: Your contributions...
tokenizer_cls = CLIPTokenizer def __init__( self, tokenizer, sequence_length=77, add_start_token=True, add_end_token=False, to_lower=True, pad_with_end_token=True, **kwargs, ): super().__init__(**kwargs) self.tokenizer = tokenizer self.sequence_length = sequence_length self.add_...
name=dataset_config)# Load tokenizer of FLAN-t5-basetokenizer = AutoTokenizer.from_pretrained(model_id)print(f"Train dataset size: {len(dataset['train'])}")print(f"Test dataset size: {len(dataset['test'])}")# Train dataset size
# pip install bitsandbytes acceleratefromtransformersimportT5Tokenizer, T5ForConditionalGeneration tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-xxl") model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-xxl", device_map="auto", load_in_8bit=True) input_text ="translate Engl...
首先,确保您尝试加载的 tokenizer 确实存在于您的环境中。由于 google/t5-v1_1-xxl 是一个预训练模型,它通常通过 Hugging Face 的 Transformers 库进行加载。 2. 执行安装命令以获取 tokenizer 如果您还没有安装 Transformers 库或者相关的 tokenizer,您可以通过以下命令进行安装: bash pip install transformers 然...
subfolder='tokenizer', cache_dir=self.cache_dir, local_files_only=True) t5_model=AutoModel.from_pretrained(t5_encoder, torch_dtype=torch.float16, cache_dir=self.cache_dir, local_files_only=True).encoder.cuda().eval() clip_model=CLIPTextModel.from_pretrained(clip_encoder, ...
**Pre/Script：**这更像是一个科学实验设计或产品开发问题，而不是一个编程问题，所以很可能有人最终...
from transformers import AutoTokenizer import numpy as np # Load dataset from the hub dataset = load_dataset(dataset_id,name=dataset_config) # Load tokenizer of FLAN-t5-base tokenizer = AutoTokenizer.from_pretrained(model_id) print(f"Traindataset size: {len(dataset['train'])}") ...
tokenizer = AutoTokenizer.from_pretrained(model_id) print(f"Train dataset size:{len(dataset['train'])}") print(f"Test dataset size:{len(dataset['test'])}") # Train dataset size: 287113 # Test dataset size: 11490 我们在配置文件中定义了一个prompt_template,其可用于来构建指令提示,以提高我...
General context for me, why do we need two tokenizers and text encoders? mattdangerw reviewed Aug 23, 2024 View reviewed changes keras_nlp/src/models/stable_diffusion_v3/t5_xxl_tokenizer.py Outdated Show resolved Collaborator Author james77777778 commented Aug 23, 2024 @mattdangerw General...