Update README.md

README.md

@@ -22,11 +22,13 @@ The concept: 8-bit quantized version of [mGPT](https://huggingface.co/ai-forever
 
 On the GPT scale, it is a similar # of parameters to GPT2-XL, but on 60+ languages.
 
+AI-Forever also released a 13B-parameter model. I made an 8-bit quantized version with weights available here: https://huggingface.co/monsoon-nlp/mGPT-13B-quantized
+
 My goal is to evaluate this on Arabic, Hindi, and Indonesian tasks, where there are fewer autoregressive language models in this size range.
 
 For English: use a GPT model or LLaMa2-7B
 
-[AI-Forever](https://huggingface.co/ai-forever) also released a 13B-parameter model, and in August 2023 added 1.3B-param models for about 1/3 of the model languages. If your language is Mongolian, for example, use mGPT-1.3B-mongol and not this one.
+In August 2023 [AI-Forever](https://huggingface.co/ai-forever) added 1.3B-param models for about 1/3 of the model's languages. If your language is Mongolian, for example, use mGPT-1.3B-mongol and not this one.
 
 ## How was the model created?
 
@@ -55,5 +57,4 @@ qmodel.save_pretrained("model_name")
 
 ## Future steps
 
-- mGPT could be further quantized (4-bit), but `model.save_pretrained()` currently throws a `NotImplementedError` error.
-- It would be great to load and quantize the 10x larger mGPT-13B, but that would take more resources.
+- mGPT could be further quantized (4-bit), but `model.save_pretrained()` currently throws a `NotImplementedError` error.