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Model: haoranli-ml/Llama-3-8B-CoPE-64k-Instruct
Source: Original Platform

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README.md

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+---
+base_model:
+- meta-llama/Meta-Llama-3-8B
+language:
+- en
+library_name: transformers
+pipeline_tag: text-generation
+license: llama3
+---
+
+## haoranli-ml/Llama-3-8B-CoPE-64k-Instruct
+
+[![Paper](https://img.shields.io/badge/CoPE_paper-A42C25?style=for-the-badge&logo=arxiv&logoColor=white)](https://arxiv.org/abs/2602.05258)
+[![GitHub](https://img.shields.io/badge/GitHub-181717?style=for-the-badge&logo=github&logoColor=white)](https://github.com/hrlics/CoPE)
+
+
+### ✨  Overview
+**CoPE** is a plug-and-play enhancement of RoPE that *softly* clips the unstable low-frequency components, delivering consistent gains both **within the training context** and during **long-context extrapolation**.
+
+With a simple yet effective soft clipping strategy, CoPE:
+
+1️⃣ **Eliminates severe OOD outliers**, whose periods exceed the pre-training context window and are the primary cause of OOD extrapolation.
+
+2️⃣ **Refines Long-range Semantic Signals** by alleviating the secret *long-term decay of semantic attention* introduced by RoPE.
+
+3️⃣ **Prevents Spectral Leakage** induced by hard frequency truncation, which otherwise leads to long-range oscillatory ringing in the attention scores across relative token distances and introduces spurious correlations.
+
+For more details on training and evaluation, please refer to the [official GitHub repository](https://github.com/hrlics/CoPE).
+
+### 📖 Citation
+```
+@article{li2026cope,
+  title={CoPE: Clipped RoPE as A Scalable Free Lunch for Long Context LLMs},
+  author={Li, Haoran and Ren, Sucheng and Yuille, Alan and Wang, Feng},
+  journal={arXiv preprint arXiv:2602.05258},
+  year={2026}
+}
+```

config.json

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+  "architectures": [
+    "LlamaForCausalLM"
+  ],
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+  "max_position_embeddings": 65536,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pad_token_id": 0,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 10000000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.44.2",
+  "use_cache": true,
+  "vocab_size": 128256
+}

generation_config.json

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+  "do_sample": true,
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+  "max_length": 4096,
+  "temperature": 0.6,
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+  "transformers_version": "4.44.2"
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