82 lines
3.7 KiB
Markdown
82 lines
3.7 KiB
Markdown
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---
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frameworks:
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- Pytorch
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license: Apache License 2.0
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base_model:
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- Qwen/Qwen2.5-14B-Instruct
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tasks:
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- text-generation
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language:
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- en
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- cn
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tags:
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- Chat
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- Instruct
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- fine-tuned
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---
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# Rombos-LLM-V2.6-Qwen-14b High-performance finetuned
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- ***同系合集 [Rombos-LLM-Qwen2.5](https://www.modelscope.cn/collections/Rombos-LLM-Qwen25-4dc8690ad7f541)***
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## Download
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SDK下载
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```bash
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#安装ModelScope
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pip install modelscope
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```
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```python
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#SDK模型下载
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from modelscope import snapshot_download
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model_dir = snapshot_download('okwinds/Rombos-LLM-V2.6-Qwen-14b')
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```
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Git下载
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```
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#Git模型下载
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git clone https://www.modelscope.cn/okwinds/Rombos-LLM-V2.6-Qwen-14b.git
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```
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# 模型简介
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本模型转载于 huggingface 上的 [rombodawg/Rombos-LLM-V2.6-Qwen-14b](https://huggingface.co/rombodawg/Rombos-LLM-V2.6-Qwen-14b)
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作者介绍到：本模型是一个基于 [Qwen/Qwen2.5-14B](https://www.modelscope.cn/models/Qwen/Qwen2.5-14B) 的 Continuous Fine-tuning 版本，并通过 [TIES-Merging](https://ar5iv.labs.arxiv.org/html/2306.01708) 方法将合并了adapter的 [Qwen/Qwen2.5-14B-Instruct](https://www.modelscope.cn/models/qwen/qwen2.5-14b-instruct) 与 [Qwen/Qwen2.5-14B](https://www.modelscope.cn/models/Qwen/Qwen2.5-14B) 进行了 TIES Merge。这使得本模型的性能优于原始的 base 模型以及 pretrain 后 fine-tune 的 Instruct 模型。
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Model tree for [okwinds/Rombos-LLM-V2.6-Qwen-14b](https://www.modelscope.cn/models/okwinds/Rombos-LLM-V2.6-Qwen-14b) </br>
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Base model - [Qwen/Qwen2.5-14B](https://www.modelscope.cn/models/Qwen/Qwen2.5-14B) </br>
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<span style="font-weight: bold;">╰</span>─ Finetuned - [Qwen/Qwen2.5-14B-Instruct](https://www.modelscope.cn/models/Qwen/Qwen2.5-14B-Instruct) </br>
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<span style="font-weight: bold;">╰</span>─ Finetuned - [本模型 okwinds/Rombos-LLM-V2.6-Qwen-14b](https://www.modelscope.cn/models/okwinds/Rombos-LLM-V2.6-Qwen-14b) </br>
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# Benchmark
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以下摘自 2024-10-29 的 Huggingface 上 [Leadboard](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) 排名数据
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本模型以 14B 参数量在总榜排名第49。截图：
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<img src="https://www.modelscope.cn/models/okwinds/Rombos-LLM-V2.6-Qwen-14b/resolve/master/HF-Leadboard-Total-2024-10-29.png" />
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在 10-32B 参数量模型中排名第7。截图：
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<img src="https://www.modelscope.cn/models/okwinds/Rombos-LLM-V2.6-Qwen-14b/resolve/master/HF-Leadboard-10-32B-2024-10-29.png" />
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在 10-20B 参数量模型中排名第1。
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<img src="https://www.modelscope.cn/models/okwinds/Rombos-LLM-V2.6-Qwen-14b/resolve/master/HF-Leadboard-10-20B-2024-10-29.png" />
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截图中的数据：
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| **Model** |**Average️**|**IFEval**|**BBH**|**MATH Lvl 5**|**GPQA**|**MUSR**|**MMLU-PRO**|
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|<span style="color:#ff6600">rombodawg/Rombos-LLM-V2.6-Qwen-14b</span>|35.89|52.14|49.22|28.85|17|19.26|48.85|
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|rombodawg/Rombos-LLM-V2.5-Qwen-14b|34.52|58.4|49.39|15.63|16.22|18.83|48.62|
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|Tsunami-th/Tsunami-1.0-14B-Instruct |34.2|78.29|49.15|0|14.21|16.34|47.21|
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|tanliboy/lambda-qwen2.5-14b-dpo-test |33.52|82.31|48.45|0|14.99|12.59|42.75|
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|jpacifico/Chocolatine-14B-Instruct-DPO-v1.2 |33.3|68.52|49.85|17.98|10.07|12.35|41.07|
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|TheTsar1209/qwen-carpmuscle-v0.2 |33.11|52.57|48.18|25|14.09|12.75|46.08|
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|microsoft/Phi-3-medium-4k-instruct |32.67|64.23|49.38|16.99|11.52|13.05|40.84|
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|TheTsar1209/qwen-carpmuscle-v0.1 |32.59|56.22|48.83|21.15|12.53|10.15|46.67|
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|v000000/Qwen2.5-Lumen-14B |32.2|80.64|48.51|0|10.4|10.29|43.36|
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|Qwen/Qwen2.5-14B-Instruct |32.18|81.58|48.36|0|9.62|10.16|43.38|
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|v000000/Qwen2.5-14B-Gutenberg-1e-Delta |32.11|80.45|48.62|0|10.51|9.38|43.67|
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|internlm/internlm2_5-20b-chat |32.08|70.1|62.83|0|9.51|16.74|33.31|
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