krpraveen/sanskrit-en-custom-transformer
translation model by krpraveen
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From the publisher
Model card & documentation
Source previewRead the publisher’s intended use, setup instructions, evaluations and limitations. The original model card is the source of truth.
A compact encoder–decoder Transformer trained from scratch on 10,000 Sanskrit–English pairs (NLU Assignment 2), with a joint SentencePiece BPE vocabulary. It is small and fast — meant to be efficient rather than to match large pretrained models. This is not a 🤗 Transformers architecture, so it ships with a self-contained modeling.py. Files: pytorchmodel.bin (weights), spm.model (tokenizer), config.json (hyperparameters), modeling.py (model + load/translate helpers). pip install gradio first. To host it, create a Hugging Face Space (SDK: Gradio) with an app.py…
Read the full model card ↗ · Preview checked 2026-10-31T12:41:27.365Z
Inside the original model card — Document outline
- Sanskrit → English — Custom Transformer (trained from scratch)
- Install
- Inference
- Use it from an open-source chat UI (Gradio)
- Notes
Headings are captured from the source. Links open the publisher’s document, not a locally hosted copy.
Documentation belongs to its respective authors. Reported project/model license: mit. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
krpraveen/sanskrit-en-custom-transformer is a translation model repository published by krpraveen on Hugging Face. A library was not reported.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- translation
- Library
- Not reported
- Recent downloads (30 days)
- 22,846
- Cumulative likes
- 0
- Hugging Face trending score
- 0
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- mit
- Access
- Not gated by Hugging Face
- Created
- 2026-07-04T11:52:42.000Z
- Last modified
- 2026-07-04T11:54:00.000Z
Compatibility and lineage
Reported languages: sa, en
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-23T06:49:06.833Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.