Instructions to use uselezzz/ruT5-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uselezzz/ruT5-summarization with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("uselezzz/ruT5-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("uselezzz/ruT5-summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +2 -1
config.json
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@@ -2,7 +2,8 @@
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"_name_or_path": "sberbank-ai/ruT5-base",
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"_num_labels": 2,
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"architectures": [
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"T5ForConditionalGeneration"
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],
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"d_ff": 3072,
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"d_kv": 64,
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"_name_or_path": "sberbank-ai/ruT5-base",
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"_num_labels": 2,
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"architectures": [
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"T5ForConditionalGeneration",
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"T5Tokenizer"
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],
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"d_ff": 3072,
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"d_kv": 64,
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