Translation
Transformers
PyTorch
Safetensors
Enawené-Nawé
Enawené-Nawé
mt5
text2text-generation
Trained with AutoTrain
Instructions to use rooftopcoder/mT5_base_English_Gujrati with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rooftopcoder/mT5_base_English_Gujrati with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="rooftopcoder/mT5_base_English_Gujrati")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("rooftopcoder/mT5_base_English_Gujrati") model = AutoModelForSeq2SeqLM.from_pretrained("rooftopcoder/mT5_base_English_Gujrati") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ecf01ad9bab47d1a144370deb3f6ebd1446dce94a9fee72005f935783db9fb0c
- Size of remote file:
- 2.33 GB
- SHA256:
- b794b0a777e36de50c0e7fbaf7e95450395449faadf8768988844294cddfcad9
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