Translation
Transformers
Safetensors
Telugu
English
t5
text2text-generation
indic-nlp
telugu
mt5
hybrid-training
full-finetune
Eval Results (legacy)
text-generation-inference
Instructions to use ManiKumarAdapala/mt5-telugu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ManiKumarAdapala/mt5-telugu 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="ManiKumarAdapala/mt5-telugu")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ManiKumarAdapala/mt5-telugu") model = AutoModelForSeq2SeqLM.from_pretrained("ManiKumarAdapala/mt5-telugu") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e014fc644c17ceafb530dcbdb2b4f99ac49de1cfddf963448275df9f4b091cde
- Size of remote file:
- 4.31 MB
- SHA256:
- ef78f86560d809067d12bac6c09f19a462cb3af3f54d2b8acbba26e1433125d6
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