Text Classification
Transformers
Safetensors
English
Chinese
qwen3_5
image-text-to-text
decision-model
system-one
decision-index
lora-merged
model-soup
Instructions to use PelaAI/KnowLine-4B-Gen2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PelaAI/KnowLine-4B-Gen2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PelaAI/KnowLine-4B-Gen2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("PelaAI/KnowLine-4B-Gen2") model = AutoModelForMultimodalLM.from_pretrained("PelaAI/KnowLine-4B-Gen2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
README.zh.md: link KnowLine-4B-Gen4
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README.zh.md
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| 模型 | 日期 | DI 0.3 公开 | DI 0.2.1 | 黄金集留出(英 / 简 / 繁) | 说明 |
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| [KnowLine-4B-Gen3](https://huggingface.co/PelaAI/KnowLine-4B-Gen3) | 2026-10-09 | 63.11 | — | 69.4 / 70.8 / 65.0 | 第三版 |
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| KnowLine-4B-Gen2(本模型) | 2026-10-08 | 62.54 | — | 69.7 / 71.2 / 64.8 | Gen1 占 0.5,mix F 第 4,500、5,000 步各占 0.25,权重平均 |
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| [KnowLine-4B-Gen1](https://huggingface.co/PelaAI/KnowLine-4B-Gen1) | 2026-10-07 | 60.47 | 60.92 | 68.7 / 69.9 / 64.1 | 首次发布(内部运行 "mix E",第 5,650 步) |
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| 模型 | 日期 | DI 0.3 公开 | DI 0.2.1 | 黄金集留出(英 / 简 / 繁) | 说明 |
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| [KnowLine-4B-Gen4](https://huggingface.co/PelaAI/KnowLine-4B-Gen4) | 2026-10-10 | 64.90 | — | 69.7 / 70.1 / 65.1 | 第四版 |
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| [KnowLine-4B-Gen3](https://huggingface.co/PelaAI/KnowLine-4B-Gen3) | 2026-10-09 | 63.11 | — | 69.4 / 70.8 / 65.0 | 第三版 |
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| KnowLine-4B-Gen2(本模型) | 2026-10-08 | 62.54 | — | 69.7 / 71.2 / 64.8 | Gen1 占 0.5,mix F 第 4,500、5,000 步各占 0.25,权重平均 |
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| [KnowLine-4B-Gen1](https://huggingface.co/PelaAI/KnowLine-4B-Gen1) | 2026-10-07 | 60.47 | 60.92 | 68.7 / 69.9 / 64.1 | 首次发布(内部运行 "mix E",第 5,650 步) |
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