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--- |
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license: apache-2.0 |
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datasets: |
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- kz-transformers/multidomain-kazakh-dataset |
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language: |
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- kk |
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pipeline_tag: fill-mask |
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library_name: transformers |
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--- |
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# Kaz-RoBERTa (base-sized model) |
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## Model description |
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## Usage |
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You can use this model directly with a pipeline for masked language modeling: |
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```python |
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>>> from transformers import pipeline |
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>>> unmasker = pipeline('fill-mask', model='kz-transformers/kaz-roberta-conversational') |
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>>> unmasker("Hello I'm a <mask> model.") |
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Here is how to use this model to get the features of a given text in PyTorch: |
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```python |
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from transformers import AutoTokenizer, AutoModelForMaskedLM |
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tokenizer = AutoTokenizer.from_pretrained("kz-transformers/kaz-roberta-conversational") |
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model = AutoModelForMaskedLM.from_pretrained("kz-transformers/kaz-roberta-conversational") |
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# prepare input |
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text = "Replace me by any text you'd like." |
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encoded_input = tokenizer(text, return_tensors='pt') |
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# forward pass |
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output = model(**encoded_input) |
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``` |
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### BibTeX entry and citation info |
