Translation
Transformers
Safetensors
Bengali
English
t5
text2text-generation
text-generation-inference
Instructions to use reyazul/BanglaSTEM-T5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use reyazul/BanglaSTEM-T5 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="reyazul/BanglaSTEM-T5")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("reyazul/BanglaSTEM-T5") model = AutoModelForSeq2SeqLM.from_pretrained("reyazul/BanglaSTEM-T5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add pipeline tag, library name, and paper link
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by nielsr HF Staff - opened
README.md
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license: apache-2.0
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language:
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- bn
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- en
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base_model:
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- csebuetnlp/banglat5_nmt_en_bn
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datasets:
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- reyazul/BanglaSTEM
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---
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base_model:
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- csebuetnlp/banglat5_nmt_en_bn
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datasets:
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- reyazul/BanglaSTEM
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language:
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- bn
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- en
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license: apache-2.0
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pipeline_tag: translation
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library_name: transformers
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---
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This model is the BanglaSTEM translation model, presented in the paper [BanglaSTEM: A Parallel Corpus for Technical Domain Bangla-English Translation](https://huggingface.co/papers/2511.03498).
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The model is a T5-based translation model specifically trained on the BanglaSTEM dataset, which consists of 5,000 carefully selected Bangla-English sentence pairs from STEM fields. It aims to improve translation accuracy for technical content, enabling Bangla speakers to effectively use English-focused language models for technical problem-solving.
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