Transformers
PyTorch
JAX
Safetensors
Russian
t5
text2text-generation
normalization
denoising autoencoder
russian
text-generation-inference
Instructions to use cointegrated/rut5-small-normalizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cointegrated/rut5-small-normalizer with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("cointegrated/rut5-small-normalizer") model = AutoModelForSeq2SeqLM.from_pretrained("cointegrated/rut5-small-normalizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
2431f32
1
Parent(s): ad5a902
Train model to loss 0.8
Browse files- config.json +1 -1
- pytorch_model.bin +1 -1
config.json
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{
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"_name_or_path": "cointegrated/rut5-small",
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"architectures": [
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"T5ForConditionalGeneration"
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{
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"_name_or_path": "cointegrated/rut5-small-normalizer",
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"architectures": [
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pytorch_model.bin
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oid sha256:9116d26775fa095bbd24b03bf28bf3d7e801e19eaedc12ae19283d23f98ed721
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size 258668061
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