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library_name: transformers
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> Update @ 2025.03.14: The updated version, [T3Q-qwen2.5-14b-v1.2-e2](https://huggingface.co/JungZoona/T3Q-qwen2.5-14b-v1.2-e2) release
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> Update @ 2025.03.14: The updated version, [T3Q-qwen2.5-32b-v1.2-e2](https://huggingface.co/JungZoona/T3Q-qwen2.5-32b-v1.2-e2) release
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## Model Summary
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T3Q-qwen2.5-14b-v1.0-e3 is a post-trained version of the Qwen/Qwen2.5-14B-Instruct-1M model.
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(LoRA-8-4-0.0001-cosine-32-16 with train_data_v1.0)
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## Global Open LLM Leaderboard Performance
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This model achieved 1st place in performance among models under 32b in the [Global Open LLM Leaderboard](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?params=0%2C32).
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<details>
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<summary>Page Capture</summary>
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<img src="https://cdn-uploads.huggingface.co/production/uploads/63e05d54a98d931aa90a7e18/r-YILW4uipdjTfEKAFG4i.png" alt="Page Capture">
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</details>
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## Quick Start
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Here provides a code snippet with `apply_chat_template` to show you how to load the tokenizer and model and how to generate contents.
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library_name: transformers
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---
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> Update @ 2025.03.14: The updated version, [**T3Q-qwen2.5-14b-v1.2-e2**](https://huggingface.co/JungZoona/T3Q-qwen2.5-14b-v1.2-e2) release
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> Update @ 2025.03.14: The updated version, [**T3Q-qwen2.5-32b-v1.2-e2**](https://huggingface.co/JungZoona/T3Q-qwen2.5-32b-v1.2-e2) release
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## Model Summary
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T3Q-qwen2.5-14b-v1.0-e3 is a post-trained version of the Qwen/Qwen2.5-14B-Instruct-1M model.
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(LoRA-8-4-0.0001-cosine-32-16 with train_data_v1.0)
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## Global Open LLM Leaderboard Performance
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This model achieved **1st place in performance among models under 32b** in the [**Global Open LLM Leaderboard**](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?params=0%2C32). [[**View Article**]](https://www.aitimes.com/news/articleView.html?idxno=168786)
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<details>
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<summary>Page Capture</summary>
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<img src="https://cdn-uploads.huggingface.co/production/uploads/63e05d54a98d931aa90a7e18/r-YILW4uipdjTfEKAFG4i.png" alt="Page Capture">
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</details>
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## Quick Start
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Here provides a code snippet with `apply_chat_template` to show you how to load the tokenizer and model and how to generate contents.
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