Transformers
TensorBoard
Safetensors
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use LegionIntel/contextual_string_normalizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LegionIntel/contextual_string_normalizer with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("LegionIntel/contextual_string_normalizer") model = AutoModelForSeq2SeqLM.from_pretrained("LegionIntel/contextual_string_normalizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from LegionIntel/contextual_string_normalizer: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/LegionIntel/contextual_string_normalizer/resolve/main/training_args.bin
- Command line
-
hf download hf://LegionIntel/contextual_string_normalizer/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/LegionIntel/contextual_string_normalizer/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 04391490c282965cc722428cfe59fd7905708be8eed2e7063d1324ad12d82ce1
- Size of remote file:
- 4.92 kB
- SHA256:
- a289793ddce01fd9f483a0d1a8ecde8d0333a63bbb8aa183d76fe59e37eca52b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.