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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| 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 |