在使用函数load_dataset()函数加载数据集时,我们需要知道加载的文件是JSON格式(类似于嵌套字典)还是JSON Lines格式(类似于包含嵌套字典的列表)。因为SQuAD-it数据集的文本都存储在data域中,因此我们可以在load_dataset()函数上设置参数field来指定取哪个域名对应的数据。 fromdatasetsimportload_datasetsquad_it_data...
I had to re-install a lot of packages, but now I get an error when I try to load the tokenizer of an HuggingFace model This is my code: # Import libraries from transformers import pipeline, AutoTokenizer # Define checkpoint model_checkpoint = 'deepset/xlm-roberta-large-squad2...
Using load_in_4bit makes the model extremely slow (with accelerate 0.21.0.dev0 and bitsandbytes 0.39.1, should be latest version and I installed from source) Using the following code from transformers import LlamaTokenizer, AutoModelForCausalLM, AutoTokenizer import torch from time import time...
warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. ' 'If you really want to use it, please modify the corresponding codes.') from gfpgan import GFPGANer import towhee @towhee.register class GFPGANerOp: def __init__(self, model_path='/GFPGAN.pth', up...
For some reason I'm noticing a very slow model instantiation time. For example to load shleifer/distill-mbart-en-ro-12-4 it takes 21 secs to instantiate the model 0.5sec to torch.load its weights. If I'm not changing how the model is created and want to quickly fast forward to the ...
(model_path,upscale,arch,channel_multiplier,bg_upsampler)def__call__(self,img):cropped_faces,restored_faces,restored_img=self._restorer.enhance(img,has_aligned=False,only_center_face=False,paste_back=True)returnrestored_faces[0][:,:,::-1](towhee.glob['path']('*.jpg').image_load['path...
0 How to download a HuggingFace model 'transformers.trainer.Trainer'? 0 Hugging Face - Could not load model facebook/bart-large-mnli 0 Wandb website for Huggingface Trainer shows plots and logs only for the first model 1 Why there are no logs and which model is saved? Hot Network Qu...
腾讯云大数据Elasticsearch Service在最近上线了8.8.1版本。该版本中的核心能力,是为AI革命提供高级搜索能力!该版本特别引入了Elasticsearch Relevance Engine™(ESRE™)—— 一款强大的AI增强搜索引擎,为搜索与分析带来全新的前沿体验。
(model_path,upscale,arch,channel_multiplier,bg_upsampler)def__call__(self,img):cropped_faces,restored_faces,restored_img=self._restorer.enhance(img,has_aligned=False,only_center_face=False,paste_back=True)returnrestored_faces[0][:,:,::-1](towhee.glob['path']('*.jpg').image_load['path...
These modelshave an interesting feature. They run well on the cloud platform, but once you want to run them locally, you have to struggle. You can always see user feedback in the GitHub associated with the project: this model and code , I can't run it locally, it's too troublesome ...