Translation
Transformers
ONNX
Nepali
English
setu_translation
feature-extraction
nepali
english
multilingual
code-mixed
romanized
devanagari
custom_code
Eval Results (legacy)
Instructions to use santoshdahal/setu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use santoshdahal/setu 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="santoshdahal/setu", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("santoshdahal/setu", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files
README.md
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@@ -57,7 +57,7 @@ The SETU model can handle:
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Ensure that you have transformers and onnx installed:
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```bash
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pip install transformers
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```
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## Usage
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If you use this model, please cite:
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```
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@misc{
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title={SETU: Script-agnostic English Translation Unifier},
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author={Santosh Dahal},
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year={
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}
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```
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Ensure that you have transformers and onnx installed:
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```bash
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pip install transformers onnxruntime
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```
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## Usage
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If you use this model, please cite:
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```
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@misc{setu2025,
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title={SETU: Script-agnostic English Translation Unifier},
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author={Santosh Dahal},
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year={2025}
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}
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```
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