Update README.md

README.md

@@ -29,18 +29,18 @@ The models are trained iteratively using an EM loop:
 1. **E-step**: Generate K=8 rationale candidates, compute rewards, select best
 2. **M-step**: Fine-tune both models on selected (concept, rationale, problem) triples
 
-- **Developed by:** [Your Name/Organization]
+- **Developed by:** Krzysztof Staroń
 - **Model type:** LoRA fine-tuned Causal Language Model
 - **Language(s):** English (mathematical reasoning)
-- **License:** Apache 2.0 (inherited from Qwen2.5-7B-Instruct)
-- **Finetuned from:** Qwen/Qwen2.5-7B-Instruct
+- **License:** Apache 2.0 (inherited from Qwen2.5-7B)
+- **Finetuned from:** Qwen/Qwen2.5-7B
 
 ### Model Sources
 
 - **Base Model:** [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct)
 - **Paper:** [PromptCoT 2.0: Scaling Prompt Synthesis for Large Language Model Reasoning](https://arxiv.org/abs/2509.19894) (arXiv:2509.19894)
 - **Authors:** Xueliang Zhao, Wei Wu, Jian Guan, Zhuocheng Gong, Lingpeng Kong
-- **Related Model:** [PromptCoT Rationale Model (qφ)](https://huggingface.co/PanzerBread/promptcot-q)
+- **Related Model:** [PromptCoT2.0](https://huggingface.co/xl-zhao/PromptCoT-2.0-Prompt-Generation-Model)
 
 ## Uses
 
@@ -95,12 +95,6 @@ This model is specialized for mathematical reasoning and may not perform well fo
 - **EM Convergence**: The EM algorithm may converge to local optima, depending on initialization and hyperparameters
 - **Generated Quality**: Generated problems may require manual validation for correctness and appropriateness
 
-### Technical Limitations
-
-- **Context Length**: Limited to 512 tokens during EM training (2048 for cold start)
-- **Sampling**: Uses temperature sampling (T=0.7) which may produce diverse but sometimes inconsistent outputs
-- **Reward Function**: The reward is based on log probabilities, which may not perfectly correlate with problem quality
-
 ### Recommendations
 
 Users should:
@@ -292,24 +286,6 @@ Zhao, X., Wu, W., Guan, J., Gong, Z., & Kong, L. (2025). PromptCoT 2.0: Scaling
 
 **Paper Link:** [https://arxiv.org/abs/2509.19894](https://arxiv.org/abs/2509.19894)
 
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
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-## More Information [optional]
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-[More Information Needed]
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-## Model Card Authors
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-[Your Name/Organization]
-
-## Model Card Contact
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-[Your Email/Contact]
-
 ### Framework versions
 
 - PEFT 0.17.1