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, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("rooftopcoder/mT5_base_English_Gujrati") model = AutoModelForMultimodalLM.from_pretrained("rooftopcoder/mT5_base_English_Gujrati") - Notebooks
- Google Colab
- Kaggle
metadata
tags:
- autotrain
- translation
language:
- unk
- unk
datasets:
- rooftopcoder/autotrain-data-en-gj
co2_eq_emissions:
emissions: 11.738270627825147
Model Trained Using AutoTrain
- Problem type: Translation
- Model ID: 54465127487
- CO2 Emissions (in grams): 11.7383
Validation Metrics
- Loss: 1.736
- SacreBLEU: 2.095
- Gen len: 18.757