Update README.md

README.md

@@ -1,55 +0,0 @@
-# 169Pi/Alpie-core
-
-## Model Summary
-`169Pi/Alpie-core` is a 32B parameter causal language model.  
-It is the **world’s first large-scale 4-bit LoRA-trained model**, optimized over **three distinct training phases** for reasoning, knowledge integration, and benchmark performance.  
-The model specializes in **mathematics, coding, science, competitive exams, Indian context, and law**.
-
----
-
-## Model Details
-- **Base Model:** `deepseek-ai/DeepSeek-R1-Distill-Qwen-32B`
-- **Architecture:** 32B parameter causal LM (chat-optimized)
-- **Quantization:** 4-bit NF4 with double quantization enabled
-- **Precision for Inference:** 4-bit NF4
-- **Frameworks:** PEFT, LoRA, bitsandbytes, PyTorch
-- **Max Context Length:** 65k tokens
-- **Deployment Framework:** vLLM
-- **License:** *(to be filled)*
-
----
-
-
----
-
-## Hyperparameters
-- **Epochs per phase:** 2
-- **Batch Size:** 256
-- **Gradient Accumulation Steps:** 4
-- **Learning Rate:** `1e-5` (initially `2e-5`, reduced to avoid early over-generalization)
-- **Scheduler:** Cosine
-- **Optimizer:** AdamW (`adamw_torch`)
-- **LoRA Rank (r):** 16
-- **LoRA Alpha:** 8
-- **LoRA Dropout:** 0.1
-- **Target Modules:** `q_proj`, `v_proj`
-
----
-
-
-
-## Intended Use
-- **Primary:** Educational tutoring, competitive exam preparation, coding assistance, legal reasoning, general knowledge Q&A.
-- **Secondary:** Research support, problem-solving in science and mathematics.
-
----
-
-## Limitations & Warnings
-- May produce inaccurate or outdated information for highly recent events.
-- Not suitable for tasks requiring legal or medical advice without expert review.
-- Performance may vary outside trained domains.
-
----
-
-## Citation
-If you use this model in your research, please cite: