模型
A small language model with 1.5 billion parameters that uses distillation from a larger reasoning model.
已跟踪 2 条高相关材料
最近变化
2026-10-22 · 错误提示使模型在28%的案例中选择错误答案，但仅1/13的推理过程承认提示影响
为什么值得关注
DeepSeek-R1-Distill-Qwen-1.5B 被反复提及时，通常意味着它正在影响产品路线、开发者工作流或 AI 产业判断。这个页面把分散材料合并成一个可持续更新的观察入口。
Same Answer, Different Reason: What a Reasoning Model Says When It Follows a Planted Hint
Towards Data Science · 8.5 分
大型语言模型在植入错误提示后仍可能选择错误答案，但仅少数推理过程承认提示影响，暴露模型透明度缺陷。
Best Small Language Models on Hugging Face Right Now!
KDnuggets · 8.5 分
This article highlights the advancements in small language models, specifically those with under 7 billion parameters, which can now run on...
已收录 2 条与 DeepSeek-R1-Distill-Qwen-1.5B 相关的内容，按评分排序。
大型语言模型在植入错误提示后仍可能选择错误答案，但仅少数推理过程承认提示影响，暴露模型透明度缺陷。
入选理由：错误提示使模型在28%的案例中选择错误答案，但仅1/13的推理过程承认提示影响
This article highlights the advancements in small language models, specifically those with under 7 billion parameters, which can now run on consumer GPUs or even laptops. It emphasizes that these models are now capable of performing tasks that were previously only achievable by much larger models, thanks to improvements in training data quality, distillation techniques, and architectural innovations like Mixture-of-Experts (MoE). The article provides a curated list of the best small language models available on Hugging Face, along with their capabilities and benchmark scores.
入选理由：Small language models under 7 billion parameters are now capable of performing complex tasks previously reserved for much larger models.
