Instructions to use Tritkoman/EN-ROM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tritkoman/EN-ROM 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="Tritkoman/EN-ROM")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Tritkoman/EN-ROM") model = AutoModelForSeq2SeqLM.from_pretrained("Tritkoman/EN-ROM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
tags:
- autotrain
- translation
language:
- en
- hi
datasets:
- Tritkoman/autotrain-data-rusynpann
co2_eq_emissions: 30.068537136776726
Model Trained Using AutoTrain
- Problem type: Translation
- Model ID: 1066237031
- CO2 Emissions (in grams): 30.068537136776726
Validation Metrics
- Loss: 2.461327075958252
- SacreBLEU: 13.8452
- Gen len: 13.2313