Alex Getmantidlige AI-signaler

DeepSeek R1

DeepSeek

Lanceret Opdateret
Kontekstvindue
64K
64.000 tokens

Tidslinje

  1. · Vægtversion · kildelink
  1. · Kildelinks · GitHub search · DeepSeek · commits · warejohn4366/war · @warejohn4366
    Uddrag
    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. · Kildelinks · GitHub search · DeepSeek · pulls · overnightworks/speech · @dependabot[bot]
    Uddrag
    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. · Kildelinks · GitHub search · DeepSeek · pulls · anomalyco/models.dev · @models-dev-automation[bot]
    Uddrag
    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. · Kildelinks · GitHub search · DeepSeek · pulls · ROCm/aiter · @karverma-amd
    Uddrag
    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. · Kildelinks · GitHub search · DeepSeek · pulls · NVIDIA/TensorRT-LLM · @moraxu
  6. · Kildelinks · GitHub search · DeepSeek · pulls · NVIDIA/TensorRT-LLM · @farazkh80
    Uddrag
    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. · Katalogpost · GitHub · openai/openai-agents-python · code
    Uddrag
    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

    Denne henvisning i koden bekræfter ikke en modelidentifikator i brug.

Signaler 1

Specifikationer

DeepSeek R1 er en model fra DeepSeek med åbne vægte, lanceret den 2025-01-20. Kontekstvinduet er 64.000 tokens.

Kontekstvindue
64.000
Vægte
Åbne

Spørgsmål

Hvor stort er kontekstvinduet for DeepSeek R1?

Kontekstvinduet er 64.000 tokens.

Er vægtene for DeepSeek R1 offentligt tilgængelige?

Ja. DeepSeek offentliggør vægtene.

Hvornår blev DeepSeek R1 lanceret?

Den 2025-01-20.