Here at TEK, we aim to provide personalized service and quality solutions that exceed your expectations. Learn more about how our experts can serve you: ow.ly/RhJ050Z7Okg
#processflow #instrumentation #piping #semiconductor #biopharma
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🚀 ProcessFlow Intelligence™ v4.0 is here.
aienginear.com/advanced-proc…
Advanced:
✔ Thermodynamics
✔ Pipe Hydraulics
✔ API RP 14E
✔ ASME VIII
✔ AI Engineering Validation
🌐 Aienginear.com
#Engineering #ProcessEngineering #ASME #API #OilAndGas #Hydraulics
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Work often slows down in the middle where clarity drops and delays begin.
VegamAI keeps execution flowing so progress stays consistent.
Start Your Free Trial - vegam.ai/register.html
#WorkflowAutomation #Operations #ProcessFlow #Execution #NoCode #Productivity #VegamAI
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May 26
Wow, so happy to know you have been doing this Bro
And tell us, how has the processflow been since you engage in that?
It saves you more hours no doubt and its non-negotaible
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May 21
09: SaaS dashboard
Color Palette:
Background:
- "#F3F4F7"
- "#ECECEC"
- "#FFFFFF"
Card:
- "#ECECEC"
- "#F5F5F5"
- "#FFFFFF"
Text:
Primary: "#111111"
Secondary: "#666666"
Light: "#FFFFFF"
Accent:
Purple: "#6C35FF"
Violet: "#7B3CFF"
SoftPurple: "#DCCEFF"
Highlight:
Mint: "#35F2B2"
Neutral:
- "#D9D9D9"
- "#BFBFBF"
- "#888888"
Layout:
Cards:
Shape: "rounded rectangles"
Radius: "24-36px"
Border: "none"
Shadow: "none"
Padding: "generous"
Visual Elements:
UI:
Style: "flat modern SaaS dashboard"
Elements:
- "progress bars"
- "data charts"
- "circular graphs"
- "stat cards"
- "timeline indicators"
- "floating labels"
- "minimal badges"
Icons:
Style: "flat minimal icons"
Shape: "rounded"
Colors:
- "#6C35FF"
- "#7B3CFF"
- "#FFFFFF"
Charts:
Style:
- "minimal axis"
- "purple highlight bars"
- "thin gray grid lines"
- "clean white chart area"
- "dashboard aesthetic"
Graphs:
- "bar charts"
- "line charts"
- "donut charts"
- "percentage circles"
- "comparison tables"
Components:
TeamCards:
Style:
- "portrait image cards"
- "minimal captions"
- "rounded corners"
- "soft gray backgrounds"
PricingCards:
Style:
- "3-column pricing layout"
- "soft purple backgrounds"
- "minimal borders"
- "center aligned"
SWOT:
Style:
- "large typography initials"
- "purple highlight quadrant"
- "clean white cards"
ProcessFlow:
Style:
- "connected circles"
- "step indicators"
- "minimal arrows"
- "horizontal workflow"
Design Rules:
- "Avoid shadows entirely"
- "Use flat minimal UI elements"
- "Favor clean white and light-gray surfaces"
- "Use purple as the primary accent color"
- "Maintain spacious modern SaaS layouts"
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7,410
May 15
We request step 2 be digitalised/streamline the processflow to avoid back and forth ..our expectation is that we are serving the whole uganda not only people in the central business district.
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Most processes don’t fail at the start, they lose momentum along the way.
VegamAI ensures work flows smoothly until completion.
Start Your Free Trial - vegam.ai/register.html
#WorkflowAutomation #Execution #Operations #ProcessFlow #NoCode #BusinessEfficiency #VegamAI
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🍀 Concentration shapes movement and direction.
📊 High density speeds interaction; dispersed allows broader growth.
🌐 KosinCapital maps patterns within operational flow.
🔍 Awareness of density ensures coherent, stable outcomes.
#KosinCapital #Density #ProcessFlow
25,058
How does your industry approach process improvement?
Which Lean Six Sigma tools could revolutionize your business?
Read article: links.elora-consulting.com/s…
#LeanSixSigmaTools #ProcessFlow #CustomerSatisfaction #OperationalSuccess #BusinessExcellence #EloraConsulting
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Primeiro modelo fine-tuned que publiquei: Qwen2.5-1.5B-ProcessFlow-v1.7-LoRA. Validacao empirica do dataset ProcessFlow — 0.681 PFE-Eval delta, PPL -4.62, HumanEval sem regressao. Apache 2.0.
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Primeiro modelo fine-tuned que eu lancei publicamente: Qwen2.5-1.5B-ProcessFlow-v1.7-LoRA.
Nao e um modelo de producao. E o RESULTADO da validacao empirica que postei mais cedo: Qwen2.5-1.5B base treinado via Unsloth LoRA r=32 em 108k samples do dataset ProcessFlow v1.7, 3 epochs no RTX PRO 6000 Blackwell.
Resultado interno: PFE-Eval subiu de 0.217 pra 0.899 ( 0.681 delta), PPL test_clean 7.258 → 2.638, HumanEval sem regressao. Todos os 3 gates de validacao passaram.
O que isso significa: o dataset ProcessFlow ENSINA de verdade. Esse modelo e a prova viva. Agora vou escalar pra batches maiores e modelos maiores (Gemma 4 31B proximo) com confianca.
Apache 2.0. Aberto pra quem quiser testar, criticar, ou tentar reproduzir.
huggingface.co/caiovicentino…
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658
Beleza, vou explicar simples:
Imagina que voce tem uma biblioteca gigante com MILHOES de livros (o "modelo de IA"). E muito pesada, nao cabe no teu celular.
O ProcessFlow e tipo um "professor paciente" que mostra como um aluno (outro modelo de IA, menor e mais leve) deve reagir quando alguem pede ajuda pra consertar um problema de programacao.
Treinei um aluno pequeno (Qwen2.5-1.5B) usando esse material do ProcessFlow e medi se ele melhorou.
Resultado: ele foi de nota 2,17 (em 10) pra nota 8,99. Acertou quase tudo, enquanto antes errava quase tudo.
Traducao: o material de ensino funciona. E dava pra escalar — ou seja, se eu usar mais material parecido, posso treinar modelos ainda melhores pra resolver problemas de codigo.
E basicamente isso: ensinei uma IA pequena a virar uma IA muito boa em arrumar bugs e escrever codigo, e provei com medicao.
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Great question, and totally get the budget pain. $100 for one 30B fine-tune is the reality of rented A100/H100 hours.
The recent game-changer for your exact situation:
**Unsloth Kaggle free notebook for Gemma 4 31B** (released 2 days ago). Kaggle gives you free GPU time (~30h/week), Unsloth squeezes the memory so 31B actually fits. Zero-cost fine-tuning of a frontier-class open-weight model.
Link: kaggle.com/code/danielhanche…
Complementary budget moves:
1. LoRA (low rank adapters) instead of full fine-tune — 10-100x less VRAM, keeps the base model frozen
2. QLoRA (4-bit quant during training) — fits bigger models on smaller GPUs
3. Start smaller — validate your pipeline on a 1.5B-3B model first (like I did with ProcessFlow on Qwen2.5-1.5B yesterday: 7h27 on one RTX 6000 for 108k samples)
A 4090 Unsloth/QLoRA gets you really far. You can fine-tune 7B-9B models comfortably at home, and use Kaggle/Colab for the occasional 31B run.
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ProcessFlow v1.7 validado: Qwen2.5-1.5B LoRA em 108k samples → 0.681 delta no PFE-Eval (0.217 → 0.899), PPL -4.62, HumanEval sem regressao. Dataset pronto pra escalar.
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Atualizacao honesta do ProcessFlow v1.7 — o dataset que publiquei ontem:
Treinei Qwen2.5-1.5B base via Unsloth LoRA r=32 em 108k samples, 3 epochs (7h27 em RTX PRO 6000 Blackwell).
Resultado do eval interno (PFE-Eval, n=180):
| Formato | Baseline | Treinado | Delta |
|---|---|---|---|
| multi_step_evolution | 0.045 | 0.872 | 0.827 (19x) |
| legacy_single_step_fix | 0.259 | 0.985 | 0.726 |
| stack_trace_debug | 0.169 | 0.860 | 0.691 |
| agent_tool_trace | 0.200 | 0.889 | 0.689 |
| security_chain | 0.183 | 0.789 | 0.606 |
| executable_test_case | 0.447 | 0.998 | 0.550 |
| **OVERALL** | **0.217** | **0.899** | ** 0.681** |
PPL no test_clean: 7.258 → 2.638 (delta -4.62 nats)
HumanEval sem regressao.
Todos os 3 gates de validacao passaram. Dataset ta validado pra escalar.
huggingface.co/datasets/caio…
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480
ProcessFlow: meu primeiro dataset publico no HuggingFace. Process-centric, pra treinar agentes de codigo. Tool-use, debugging, refactoring, chain-of-thought. Validado empiricamente em Qwen2.5-1.5B. Apache-2.0.
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Acabei de publicar meu primeiro dataset no HuggingFace: ProcessFlow.
E um dataset process-centric pra treinar agentes de codigo. Foco em tool-use, debugging, refactoring, postmortem e chain-of-thought de processo longo.
Tamanho: 100K-1M samples. Multi-formato (messages, alpaca, sharegpt) pra plugar em qualquer pipeline de fine-tune.
Empiricamente validado: Qwen2.5-1.5B base fine-tuned no v1.7 com LoRA r=32, 3 epochs → delta de 0.681 no ProcessFlow-Eval (0.217 → 0.899), sem regressao no HumanEval, PPL -4.62 nats no test set.
Apache-2.0. Bora descentralizar o treinamento de agentes.
huggingface.co/datasets/caio…
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431
From silo to process line, pneumatic conveying connects your plant with air as the medium. How streamlined is your material flow today?
#PneumaticConveying #BulkHandling #ProcessFlow #SmartFactory
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