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Fiverr Pro
English
$
USD
I will build custom solutions, ai model deployment for production
About this Gig
What we do
- Fine-tune or train from scratch for vision, NLP, tabular, time series, and audio
- Reproducible code with tracked runs
Key services
- Data Audit: fast EDA, leakage checks, class balance, split plan
- Preprocessing: cleaning, transforms, tokenization/normalization
- HPO: targeted trials with early stopping/pruning
- Evaluation: F1, ROC-AUC, mAP, mIoU, MAE, WER + error analysis
- Model Export: PyTorch weights + ONNX (TFLite/Core ML on request)
- Dockerized REST API (optional): FastAPI endpoints, OpenAPI docs
- CI/CD & Monitoring (optional): pipelines, metrics, drift alerts
Process
- Discovery target metric, latency limits
- Data prep splits & augmentations
- Training HPO & ablations
- Validation explainability when relevant
- Handover deployment support
Stack
PyTorch, TensorFlow, HF, scikit-learn, Optuna, MLflow, ONNX/TensorRT, Docker/FastAPI
Ownership
You own code and weights. Cloud GPU costs billed at provider rates. NDA/white-label available.
To start
- Goal & metric, data link/schema, constraints, deploy preference, deadline, compute budge
Programming language:
Python
•
MATLAB
•
Colab
•
MLflow
•
Julia
Frameworks:
Scikit-learn
•
DeepPy
•
Keras
•
PyTorch
•
Panda
•
TensorFlow
FAQ
Will you sign an NDA?
Yes. I’m comfortable with NDA and/or a mutual confidentiality clause. White-label work is also fine.
How do you protect my data?
Least-privilege access, private repos, encrypted storage (when cloud is used), and no third-party sharing. I delete datasets and artifacts on request or 14 days post-handover.
Who owns the model and code?
You do. Full transfer of trained weights, source code, and docs. Note: base models/open-source libs retain their original licenses.
What are typical delivery timelines?
Basic: 7 days, Standard: 14 days, Premium: 28 days. Extra-fast options are available in Extras.
What can impact timelines?
Data size/quality, labeling, number of HPO trials, compliance requirements, and deployment complexity (cloud, scaling, security).
Can you deploy the model for production use?
Yes. Premium includes cloud deployment; Standard ships an API skeleton. I can provide a Dockerized REST API with health checks and docs.
Which stacks do you support?
PyTorch/TensorFlow, Hugging Face, ONNX/TensorRT, FastAPI + Docker. I integrate with AWS/GCP/Azure, Vercel/DO, or your on-prem.
Do I get exports for mobile/edge?
Yes, Model Export to ONNX; TFLite/Core ML on request, subject to model compatibility.
What’s included in documentation?
Setup notes, run commands, endpoint specs, evaluation report, and a model card covering metrics, data, and limitations.
Do you provide maintenance?
Yes. Optional monthly maintenance (bug fixes, small updates) is available as an Extra or a custom plan.
