NLLB-200 Distilled 600M — FP16 Half Precision

🌐 Live Web Demo: Try 100% offline in your browser at huggingface.co/spaces/rudrakshrakeshzodage/nllb-200-onnx-browser-demo

This model is part of a suite of optimized/quantized versions of the base model. Other variants in this direction:

FP32 (Full Precision / Base): rudrakshrakeshzodage/nllb-200-distilled-600M-fp32

FP16 (Half Precision): rudrakshrakeshzodage/nllb-200-distilled-600M-fp16 (Current)

INT8 (Dynamic Quantization - CPU): rudrakshrakeshzodage/nllb-200-distilled-600M-int8-cpu

NF4 (4-bit GPU Quantization): rudrakshrakeshzodage/nllb-200-distilled-600M-nf4-4bit-gpu

Base model: facebook/nllb-200-distilled-600M
Precision: FP16 (16-bit Float Half Precision)
Languages: 200 (all NLLB-200 supported languages)

🏗️ Detailed Tokenizer & Model Architecture Pipeline

💾 Model Size Reduction Comparison (FP32 vs FP16 vs INT8 vs NF4)

📈 200+ Language Performance Benchmark Chart

📜 Citation & Credits

Quantization research, engineering, and benchmarking developed by Rudraksh Rakesh Zodage:

Hugging Face: rudrakshrakeshzodage
GitHub: RudrakshRakeshZodage
LinkedIn: rudraksh-zodage-
Email: Rudrakshrakeshzodage@gmail.com

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Safetensors

Model size

0.6B params

Tensor type

F32

Model tree for rudrakshrakeshzodage/nllb-200-distilled-600M-fp16

Base model

facebook/nllb-200-distilled-600M

Quantized

(28)

this model