DeepSeek R1

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1. 2025-01-20 · 가중치 버전 · 근거 링크

1. 2026-11-13T18:48:53.232Z · 근거 링크 · GitHub search · DeepSeek · commits · warejohn4366/war · @warejohn4366
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   随着AI发展，企业和开发者希望快速应用AI模型。本文介绍在阿里云PAI Model Gallery上零代码一键部署DeepSeek-V3和DeepSeek-R1模型的方法，包括准备工作、部署步骤、调用方式等。这种方式简化流程、提高效率、降低成本，助力AI能力落地。

2. 2026-11-13T18:47:56.425Z · 근거 링크 · GitHub search · DeepSeek · pulls · overnightworks/speech · @dependabot[bot]
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   XTX, <a href="https://redirect.github.com/vllm-project/vllm/issues/59774">#59774</a>); and gfx1250 enablement for gpt-oss-120b, DeepSeek-R1, DeepSeek-V4-Flash and MiniMax-M3 (<a href="https://redirect.github.com/vllm-project/vllm/issues/58800">#58800</a>).</li>

3. 2026-11-13T18:47:56.425Z · 근거 링크 · GitHub search · DeepSeek · pulls · anomalyco/models.dev · @models-dev-automation[bot]
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   Instruct-Turbo`, `openai/gpt-oss-120b-Turbo`, `google/gemma-4-31B-it-Ultra`, `mattshumer/Reflection-Llama-3.1-70B`, `NovaSky-AI/Sky-T1-32B-Preview`, `deepseek-ai/DeepSeek-R1`, `Qwen/Qwen2-7B-Instruct`, `Qwen/QwQ-32B`, `google/gemma-2-9b-it`, `google/gemma-4-31B-it-turbo`, `Qwen/Qwen3.5-0.8B`, `deepseek-ai/DeepSeek-V3-0324-Turbo`, `openbmb/MiniCPM-Llama3-V-2_5`, `microsoft/phi-4`, `inclusionAI/Ling-3.0-flash-VL`, `Qwen/Qwen3-VL-30B-A3B-Thinking`, `MiniMaxAI/MiniMax-M2.7-Turbo`, `deepseek-ai

4. 2026-11-13T18:47:56.425Z · 근거 링크 · GitHub search · DeepSeek · pulls · ROCm/aiter · @karverma-amd
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   Tuned configs for DeepSeek-R1 MLA-absorb bmms (B=128). Previously fell back to DEFAULT (untuned): 5.5x slower at decode M~1536 . Lets the BF16 MLA-absorb path run

5. 2026-11-13T18:47:56.425Z · 근거 링크 · GitHub search · DeepSeek · pulls · NVIDIA/TensorRT-LLM · @moraxu
6. 2026-11-13T18:47:56.425Z · 근거 링크 · GitHub search · DeepSeek · pulls · NVIDIA/TensorRT-LLM · @farazkh80
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   with all of its KV remote and MLA (DeepSeek-R1 shape) 1.43x, which is why allocation and placement keep pages local. Partitioned attention rejects FlashMLA, beam

7. 2026-11-10T17:59:50.472Z · 카탈로그 등록 · GitHub · openai/openai-agents-python · code
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   object="chat.completion.chunk", choices=[Choice(index=0, delta=delta)], ) for delta in [*reasoning_deltas, ChoiceDelta(content="answer")] ] events = await _collect_handler_events(*chunks, model="deepseek-r1") completed_event = next(event for event in events if event.type == "response.completed") reasoning_item = completed_event.response.output[0] assert isinstance(reasoning_item, ResponseReasoningItem) assert reasoning_item.summary[0].text == "summary" assert reasoning_item.content assert [part.text for part in reasoning_item.content] == ["raw"] assert "_chat_completions_reasoning_field" not in cast(Any, reasoning_item).provider_data replayed_messages = Converter.items_to_messages( [item.model_dump() for item in completed_event.response.output], model="deepseek-r1", ) assert len

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