Translation
Transformers
Safetensors
ONNX
m2m_100
text2text-generation
nllb-200
nllb
quantization
int8
4-bit precision
nf4
bitsandbytes
transformers-js
multilingual
neural-machine-translation
meta
seq2seq
Instructions to use rudrakshrakeshzodage/nllb-200-distilled-600M-fp32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rudrakshrakeshzodage/nllb-200-distilled-600M-fp32 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="rudrakshrakeshzodage/nllb-200-distilled-600M-fp32")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("rudrakshrakeshzodage/nllb-200-distilled-600M-fp32") model = AutoModelForSeq2SeqLM.from_pretrained("rudrakshrakeshzodage/nllb-200-distilled-600M-fp32", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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