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tan-ta
Deepakvictor/tan-ta
tan-ta is a translation model from Deepakvictor. Use it when you need text moved from one language to another. It is set up for transformers. The card lists the license as creativeml-openrail-m.
This model is Finetuned on Facebook's m2m model to convert Tanglish words to Tamil Model is finetuned on facebook/m2m100418M m2m100418m page -- https://huggingface.co/facebook/m2m100418M
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At a glance
- Task
- Translation
- Library
- transformers
- License
- creativeml-openrail-m
- Model type
- m2m_100
- Access
- Public
- Created
- Aug 14, 2023
- Updated
- Nov 27, 2023
- SHA
- 859c7fa6
Try a prompt
Model card
From the Hugging Face model README
Model Card for Deepakvictor/tan-ta
<!-- Provide a quick summary of what the model is/does. -->This model is Finetuned on Facebook's m2m model to convert Tanglish words to Tamil
Model Details
Model is finetuned on facebook/m2m100_418M m2m100_418m page --> https://huggingface.co/facebook/m2m100_418M
Model Description
<!-- Provide a longer summary of what this model is. -->- Developed by: Deepakvictor
- Language(s) (NLP): Tamil,Tanglish
- Finetuned from model [facebook/m2m100_418M]: [https://huggingface.co/facebook/m2m100_418M]
Model Sources
<!-- Provide the basic links for the model. -->- Repository: [Need to be uploaded]
- Demo [optional]: [Need to be uploaded]
How to Get Started with the Model
Use the code below to get started with the model.
# Load model directly from transformers library
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("Deepakvictor/tan-ta")
model = AutoModelForSeq2SeqLM.from_pretrained("Deepakvictor/tan-ta")
#pass the input
inp = tokenizer("Thalaivaru nirantharam",return_tensors="pt")
out= model.generate(**inp)
tokenizer.batch_decode(out,skip_special_tokens=True)
#['தலைவரு நிரந்தரம்']
Repo code --> github.com/devic1 🖤
- Task
- Translation
- Library
- transformers
- Type
- m2m_100
- License
- creativeml-openrail-m
- Languages
- ta, en
- Created
- Aug 14, 2023
- Updated
- Nov 27, 2023