模型:
kz-transformers/kaz-roberta-conversational
You can use this model directly with a pipeline for masked language modeling:
>>> from transformers import pipeline >>> unmasker = pipeline('fill-mask', model='kz-transformers/kaz-roberta-conversational') >>> unmasker("Hello I'm a <mask> model.") Here is how to use this model to get the features of a given text in PyTorch: ```python from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("kz-transformers/kaz-roberta-conversational") model = AutoModelForMaskedLM.from_pretrained("kz-transformers/kaz-roberta-conversational") # prepare input text = "Replace me by any text you'd like." encoded_input = tokenizer(text, return_tensors='pt') # forward pass output = model(**encoded_input)