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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 82820c9bb7cf577894de2ffb77dda35ac604fb67038a980e3f8ea51ff2ec9395
- Size of remote file:
- 16.3 MB
- SHA256:
- 65c2d7defb6472fada8a935bb364ae3433f7451780c8a59ab6b3cfbaadb32608
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