정보에 대해서DeepSeek-R1-Distill-Llama-70B
DeepSeek-R1-Distill-Llama-70B는 Llama-3.3-70B-Instruct를 기반으로 한 증류 Model입니다. DeepSeek-R1 시리즈의 일부로, DeepSeek-R1에서 생성된 샘플을 사용하여 미세 조정되었으며 수학, 프로그래밍 및 추론 작업 전반에서 뛰어난 성능을 보여줍니다. 이 Model은 AIME 2024, MATH-500 및 GPQA Diamond를 포함한 다양한 벤치마크에서 인상적인 결과를 달성하여 강력한 추론 능력을 입증합니다.
Explore how DeepSeek-V3's advanced reasoning and coding capabilities translate into real-world applications.
Automated Code Generation & Debugging
Generate, optimize, and debug complex code snippets across various programming languages. The model's strong reasoning helps identify logical errors and suggest efficient solutions.
Use Case Example:
"A software engineer used DeepSeek-V3 to refactor a legacy Python module, resulting in a 40% reduction in code complexity and a 25% improvement in execution speed."
Scientific & Mathematical Research
Assist researchers by solving complex mathematical problems, formulating hypotheses, and analyzing data. Its ability to reason through abstract concepts makes it a powerful tool for scientific discovery.
Use Case Example:
"A physicist modeled a complex quantum mechanics problem, and the model provided a step-by-step derivation that led to a novel insight, which was later verified experimentally."
Intelligent Agent & Tool Integration
Build sophisticated AI agents that can understand user requests, select the appropriate tools (e.g., APIs, databases), and execute multi-step tasks autonomously.
Use Case Example:
"An automated travel assistant powered by DeepSeek-V3 booked a complete itinerary by interacting with flight, hotel, and car rental APIs based on a single natural language request from the user."
Advanced Conversational AI
Create highly engaging and context-aware chatbots, virtual assistants, or role-playing characters for gaming and entertainment. The model excels at maintaining coherent and natural-sounding dialogue.
Use Case Example:
"A gaming company implemented an NPC (Non-Player Character) using the model, which provided dynamic, unscripted interactions that significantly enhanced player immersion."
메타데이터
사양
주
Deprecated
건축
교정된
아니요
전문가의 혼합
아니요
총 매개변수
70B
활성화된 매개변수
추론
아니요
Precision
FP8
콘텍스트 길이
33K
Max Tokens
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Max output:
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Input:
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Output:
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Total Context:
164K
Max output:
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Input:
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Max output:
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Input:
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/ M Tokens
Output:
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Total Context:
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Max output:
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Input:
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Output:
$
0.1
/ M Tokens
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Total Context:
33K
Max output:
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Input:
$
0.05
/ M Tokens
Output:
$
0.05
/ M Tokens
