u/prompts360
Expert · 1265 points · level 5 of 6
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Fix Repetitive Output in DeepSeek-V3
Instead of tuning legacy frequencypenalty or presencepenalty parameters on frontier models like DeepSeek-V3, fix repetitive output by adding explicit structural progression rules to the prompt. …
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Control DeepSeek-R1 Answer Verbosity After Thinking
While R1's internal <think> chain should not be artificially budget-capped in the prompt, explicitly specify the desired length and structure of the final post-</think> copy. …
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Code Migration: DeepSeek-V3 Translate, R1 Verify
Combine prompt chaining with DeepSeek's dual model families: use fast DeepSeek-V3 to translate code syntax, then pass the source and target snippets to DeepSeek-R1 to verify semantic equivalence. …
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DeepSeek-R1 Prompt to Audit Causal Claims in Papers
Use DeepSeek-R1 at temperature=0.5 with a single-instruction zero-shot prompt to evaluate statistical validity in draft manuscripts. …
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Property-Based Test Generation With DeepSeek-R1
Leverage DeepSeek-R1's internal problem decomposition and re-verification cycle to uncover subtle boundary bugs in parser implementations. …
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Generate Cold-Start CoT Fine-Tuning Data With R1
DeepSeek's training pipeline uses CoT data generated by R1-Zero/R1 for supervised fine-tuning (SFT). Prompt DeepSeek-R1 at temperature=0.6 to generate clean problem-decomposition and multi-verification traces to train sm
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Fix DeepSeek-R1 Stalling on Contradictory Instructions
Thoughtology analysis found that while DeepSeek-R1 adapts to user input when contradictions arise, this comes at the cost of efficiency because the model spends significant compute time deliberating over user intentions.
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Self-Hosted DeepSeek-R1 on vLLM for Sensitive Data
Mozilla AI's evaluation notes that because managed APIs send data to external servers, organizations handling sensitive code or clinical records should deploy DeepSeek-R1 on self-hosted vLLM Kubernetes clusters with temp
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Extract Clean Structured Output After DeepSeek think
Because DeepSeek-R1 outputs its deliberation inside <think> tags before the final answer, instruct the model in a single zero-shot prompt to emit valid JSON immediately after the closing </think> tag so your parser can s
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Tree-of-Thought Prompting With DeepSeek-V3
On non-reasoning models like DeepSeek-V3, a Tree-of-Thought (ToT) prompt structures reasoning like a decision tree to explore multiple potential solutions simultaneously before reaching a conclusion. …
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DeepSeek-R1 Factual Mode at Temperature 0.5
When using DeepSeek-R1 for legal or compliance analysis where factual precision is preferred over exploratory breadth, set temperature = 0.5 and topp = 0.95. …
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DeepSeek-V3 Domain Vocabulary Anchoring With Few-Shot
On non-reasoning models like DeepSeek-V3, providing 2 to 5 worked few-shot examples remains highly valuable when the task uses domain-specific vocabulary or an unusual output format, putting your strongest, most represen
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Vertex AI Prompt Regression Testing With Versions
Save and version proven prompts in code alongside the exact model version they were tested on, and judge any prompt change against a fixed evaluation set rather than a single good answer. …
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Gemini Prompt to Remove Jargon From Stakeholder Updates
Google's Workspace guide emphasizes stating requests in brief, specific language while avoiding jargon. …
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Gemini Customer Reply Drafts Grounded in Workspace
Combine natural-language full sentences with @[File Name] tags to draft accurate customer replies without leaving the Gmail side panel. …
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Gemini: Turn Architecture Diagrams Into Terraform
Reference both visual topology diagrams and text policy rules as equal-class inputs in Gemini 3. …
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Gemini Prompt for Hunting Anomalies in Security Logs
Top-load large log exports into <context> and place the analytical query at the bottom with an explicit bridging phrase. …
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Gemini Shortcut Discovery for Data Pipeline Optimization
Use Gemini 3's planning step #3 (Identify tools, shortcuts, or "power user" methods that solve the problem better than standard approaches) to optimize slow data processing code. …
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Gemini Clinical Protocol Check With Abstention Rules
Pair bottom-anchored long-context instructions with an explicit "I don't know" rule when querying clinical reference documents. …
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Gemini Executive Summary Plus Detail Format
Use Gemini 3's recommended <outputformat> structure to enforce an Executive Summary followed by a Detailed Response for engineering architecture reviews. …
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Gemini UI Bug Triage From Screen Recording and Logs
Pass screen recordings and text logs as equal-class inputs in Gemini 3 and prompt for cross-modal synthesis. …
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Gemini Prompt to Audit Missing Data in Forecasts
Combine Gemini 3's <constraints> and self-critique steps to ensure any missing financial inputs are explicitly flagged rather than silently interpolated. …
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Markdown-Only Prompting for Gemini Technical Docs
If you prefer Markdown over XML for a Gemini 3 prompt, adhere strictly to the single-format consistency rule by using Markdown headings (#, ##) exclusively without mixing in XML tags. …
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Summarize Strategy Sessions Across Drive Files With Gemini
After exporting a Gemini Advanced draft to Google Docs, use the Docs side panel to pull in detailed summaries from existing Google Drive files via @file name tags. …
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Vertex AI Gemini: Zero-Shot vs Few-Shot Ideation
While zero-shot prompting (providing a direct instruction without examples) works well for initial idea generation, use varied, consistent examples separated from instructions via XML tags when exact format and style mat