Update README.md

I added new models that have come out trained with the GPT-NeoX library. The library itself is sufficiently well-used that simply listing all citing papers is rapidly becoming non-viable. I'm currently leaning towards providing a curated list of "exciting" papers? I haven't looked at other libraries to see what they do yet.

README.md

@@ -736,7 +736,7 @@ The following publications by other research groups use this library:
 The following models were trained using this library:
 
 ### English LLMs
-- EleutherAI's [GPT-NeoX-20B](https://huggingface.co/EleutherAI/gpt-neox-20b), [Pythia (70M through 13B)](https://github.com/EleutherAI/pythia), and [LLeMMA (34B)](https://arxiv.org/abs/2310.10631)
+- EleutherAI's [GPT-NeoX-20B](https://huggingface.co/EleutherAI/gpt-neox-20b) and [Pythia (70M through 13B)](https://github.com/EleutherAI/pythia)
 - CarperAI's [FIM-NeoX-1.3B](https://huggingface.co/CarperAI/FIM-NeoX-1.3B)
 - StabilityAI's [StableLM (3B and 7B)](https://github.com/Stability-AI/StableLM)
 - Together.ai's [RedPajama-INCITE (3B and 7B)](https://together.ai/blog/redpajama-models-v1)
@@ -747,25 +747,29 @@ The following models were trained using this library:
 ### Non-English LLMs
 - EleutherAI's [Polyglot-Ko (1.3B through 12.8B)](https://github.com/EleutherAI/polyglot) (Korean)
 - Korea University's [KULLM-Polyglot (5.8B and 12.8B)](https://github.com/nlpai-lab/KULLM) (Korean)
-- Stability AI's [Japanese Stable LM (7B)](https://huggingface.co/stabilityai/japanese-stablelm-base-alpha-7b)
+- Stability AI's [Japanese Stable LM (7B)](https://huggingface.co/stabilityai/japanese-stablelm-base-alpha-7b) (Japanese)
 - LearnItAnyway's [LLaVA-Polyglot-Ko (1.3B)](https://huggingface.co/LearnItAnyway/llava-polyglot-ko-1.3b-hf) (Korean)
 - Rinna Co.'s [japanese-gpt-neox-3.6b](https://huggingface.co/rinna/japanese-gpt-neox-3.6b) (Japanese) and [bilingual-gpt-neox-4b](https://huggingface.co/rinna/bilingual-gpt-neox-4b) (English / Japanese)
 - CyberAgent's [Open-CLM (125M through 7B)](https://huggingface.co/cyberagent/open-calm-7b) (Japanese)
 - The Hungarian Research Centre for Linguistics's [PULI GPTrio (6.7B)](https://huggingface.co/NYTK/PULI-GPTrio) (Hungarian / English / Chinese)
 - The University of Tokyo's [weblab-10b](https://huggingface.co/Kojima777/weblab-10b) and [weblab-10b-instruct](https://huggingface.co/Kojima777/weblab-10b-instruction-sft) (Japanese)
 - nolando.ai's [Hi-NOLIN (9B)](https://blog.nolano.ai/Hi-NOLIN/) (English, Hindi)
+- Renmin University of China's [YuLan (12B)](https://huggingface.co/yulan-team/YuLan-Base-12b) (English, Chinese)
+- The Basque Center for Language Technology's [Latixna (70B)](https://huggingface.co/HiTZ/latxa-70b-v1.2) (Basque)
 
 ### Code Models
 - Carnegie Mellon University's [PolyCoder (160M through 2.7B)](https://github.com/VHellendoorn/Code-LMs) and [CAT-LM (2.7B)](https://huggingface.co/nikitharao/catlm)
 - StabilityAI's [StableCode (1.3B)](https://stability.ai/blog/stablecode-llm-generative-ai-coding) and [StableCode-Completion-Alpha (3B)](https://stability.ai/blog/stablecode-llm-generative-ai-coding)
 - CodeFuse AI's [CodeFuse (13B)](https://huggingface.co/codefuse-ai/CodeFuse-13B)
 
 ### AI for Science
+- EleutherAI's [LLeMMA (34B)](https://arxiv.org/abs/2310.10631)
 - Oak Ridge National Lab's [FORGE (26B)](https://github.com/at-aaims/forge)
-- Oak Ridge National Lab and EleutherAI's [Unnamed Material Science Domain Models (7B)](https://github.com/at-aaims/forge)
+- Oak Ridge National Lab's [Unnamed Material Science Domain Models (7B)](https://arxiv.org/abs/2402.00691)
 - Pacific Northwest National Lab's [MolJet (undisclosed size)](https://openreview.net/pdf?id=7UudBVsIrr)
 
 ### Other Modalities
+-  Rinna Co.'s [PSLM (7B)](https://arxiv.org/abs/2406.12428) (speech / text)
 -  University College London's [ChessGPT-3B](https://huggingface.co/Waterhorse/chessgpt-base-v1)
 -  Gretel's [Text-to-Table (3B)](https://huggingface.co/gretelai/text2table)