Translation
Transformers
Safetensors
gemma3_text
text-generation
machine-translation
english-to-indic
indic
multilingual
gemma-3
gemma3
bpcc
ai4bharat
flash-attention
bfloat16
text-generation-inference
Instructions to use ManiKumarAdapala/Gemma3-En2Indic-NMT-270M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ManiKumarAdapala/Gemma3-En2Indic-NMT-270M 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/Gemma3-En2Indic-NMT-270M")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ManiKumarAdapala/Gemma3-En2Indic-NMT-270M") model = AutoModelForCausalLM.from_pretrained("ManiKumarAdapala/Gemma3-En2Indic-NMT-270M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Welcome to the community
The community tab is the place to discuss and collaborate with the HF community!