Create README.md

README.md

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+---
+license: llama3.3
+datasets:
+- allenai/c4
+language:
+- en
+base_model:
+- meta-llama/Llama-3.3-70B-Instruct
+---
+
+
+# Overview
+This document presents the evaluation results of `DeepSeek-R1-Distill-Llama-70B`, a **4-bit quantized model using GPTQ**, evaluated with the **Language Model Evaluation Harness** on the **ARC-Challenge** benchmark.
+
+
+## ⚙️ Model Configuration
+
+- **Model:** `Llama-3.3-70B-Instruct`
+- **Parameters:** `70 billion`
+- **Quantization:** `4-bit GPTQ`
+- **Source:** Hugging Face (`hf`)
+- **Precision:** `torch.float16`
+- **Hardware:** `NVIDIA A100 80GB PCIe`
+- **CUDA Version:** `12.4`
+- **PyTorch Version:** `2.6.0+cu124`
+- **Batch Size:** `1`
+
+
+📌 **Interpretation:**
+- The evaluation was performed on a **high-performance GPU (A100 80GB)**.
+- The model is significantly larger than the previous 8B version, with **GPTQ 4-bit quantization reducing memory footprint**.
+- A **single-sample batch size** was used, which might slow evaluation speed.
+
+---
+
+
+📌 Let us know if you need further analysis or model tuning! 🚀