Translation
Transformers
Safetensors
English
Lushai
m2m_100
text2text-generation
machine-translation
low-resource
mizo
qlora
facebook/nllb-200-distilled-600M
8-bit precision
bitsandbytes
Instructions to use flt7007/mbart-mizo-merged with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flt7007/mbart-mizo-merged 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="flt7007/mbart-mizo-merged")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("flt7007/mbart-mizo-merged") model = AutoModelForSeq2SeqLM.from_pretrained("flt7007/mbart-mizo-merged", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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