Update README.md

README.md

@@ -19,7 +19,7 @@ Alpie-Core is one of the world's first fine-tuned 4-bit reasoning models, provin
 - **Context Length**: 65,536 tokens
 - **Max Output Length**: 16,384 tokens
 - **License**: Apache 2.0
-- **Memory Footprint**: ~8GB (75% reduction from full-precision)
+
 
 ## 3. Model Features
 
@@ -47,11 +47,11 @@ Alpie-Core is one of the world's first fine-tuned 4-bit reasoning models, provin
 | Benchmark | Alpie-Core (32B-4bit) | DeepSeek-V2 (236B) | Qwen2.5 72B | Llama 3.1 405B | Llama 3.1 70B | Gemma-3 27B-PT | Mistral-Small-24B-Base-2501 |
 |-----------|----------------------|-------------------|-------------|---------------|---------------|----------------|----------------------------|
 | MMLU (5-shot) | **81.28%** | 78.4% | 85.0% | 84.4% | 79.3% | 78.6% | 80.73% |
-| GSM8K (8-shot) | **92.75%** | 81.6% | 88.3% | 83.5% | nan | 82.2% | 80.73% |
-| BBH (3-shot) | **85.12%** | 78.8% | 79.8% | 82.9% | 81.6% | 77.7% | nan |
+| GSM8K (8-shot) | **92.75%** | 81.6% | 88.3% | 83.5% | - | 82.2% | 80.73% |
+| BBH (3-shot) | **85.12%** | 78.8% | 79.8% | 82.9% | 81.6% | 77.7% | - |
 | MMLU-Pro (5-shot) | **64.78%** | 51.4% | 58.3% | 52.8% | 53.8% | 52.2% | 54.37% |
-| MBPP (pass@1) | **75.20%** | 65.0% | 72.6% | 68.4% | nan | 65.6% | 69.64% |
-| HumanEval (pass@1) | **57.23%** | 43.3% | 53.0% | 54.9% | nan | 48.8% | nan |
+| MBPP (pass@1) | **75.20%** | 65.0% | 72.6% | 68.4% | - | 65.6% | 69.64% |
+| HumanEval (pass@1) | **57.23%** | 43.3% | 53.0% | 54.9% | - | 48.8% | - |
 
 ### SWE-Bench Verified Performance