You will get Gemini Model Fine-Tuning & Optimization for Enterprise Use Cases
Top Rated
Project details
What sets this project apart is a specialised focus on Supervised Fine-Tuning (SFT) to bridge the gap between generic AI and enterprise-grade intelligence. I help organisations move beyond basic prompting to build models that master their specific domain language across Text, Documents, Code, Images, and Audio.
Why Choose This Project?
1. Expert tuning for high-value tasks like Visual Inspection, Product Catalogue Enhancement, and Technical Audio Transcription.
2. I specialise in transforming raw data into the high-quality JSONL datasets required for Gemini to identify key attributes and categories accurately.
3. I design Proof of Concept (POC) implementations specifically to gain stakeholder buy-in, demonstrating measurable ROI in tasks like RAG optimisation and automated code review.
4. My methodology follows the core "Supervised fine-tuning Gemini process," ensuring high helpfulness and accuracy for your specific business use cases.
Why Choose This Project?
1. Expert tuning for high-value tasks like Visual Inspection, Product Catalogue Enhancement, and Technical Audio Transcription.
2. I specialise in transforming raw data into the high-quality JSONL datasets required for Gemini to identify key attributes and categories accurately.
3. I design Proof of Concept (POC) implementations specifically to gain stakeholder buy-in, demonstrating measurable ROI in tasks like RAG optimisation and automated code review.
4. My methodology follows the core "Supervised fine-tuning Gemini process," ensuring high helpfulness and accuracy for your specific business use cases.
AI Algorithms
Large Language Model, Transformer ModelAI Applications
AI Chatbot, AI Content Creation, AI Text-to-Image, AI-Generated Art, AI-Generated Code, Image Analysis, Image ProcessingAI Development Language
PythonAI Tools
Hugging Face, PyTorch, Streamlit, TensorFlowAI Models
BERTWhat's included
| Service Tiers |
Starter
$150
|
Standard
$800
|
Advanced
$2,999
|
|---|---|---|---|
| Delivery Time | 7 days | 15 days | 30 days |
Number of Revisions | 1 | 2 | 5 |
AI Model Integration | - | - | - |
Batch Normalization | - | - | - |
Database Integration | - | - | - |
Detailed Code Comments | - | ||
Image Upscaling | - | - | - |
MLOps | - | - | - |
Model Deployment | - | - | - |
Model Documentation | - | ||
Model Monitoring | - | - | - |
Model Testing & Optimization | - | ||
Model Tuning | |||
Natural Language Processing | |||
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | |||
Setup File | - | - | - |
Source Code |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$200 - $1,000
Additional Revision
+$200Frequently asked questions
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About Sani
Machine Learning Engineer | Generative AI Engineer | Cloud Engineer
100%
Job Success
Guwahati assam, India - 11:22 am local time
I am passionate about solving complex problems and making a positive impact. I bring experience across various projects, specialising in Machine Learning, Generative AI, and Cloud solutions. My expertise includes leveraging tools and frameworks such as Pandas, Matplotlib, Seaborn, Scikit-Learn, OpenCV, TensorFlow, PyTorch, Hugging Face Transformers, LangChain, ChatGPT, Gemini, Llama, Cohere, Pinecone, LlamaIndex, and more to build innovative solutions.
I am an AWS Certified Generative AI Developer Professional, AWS Certified Machine Learning Engineer Associate, AWS Certified AI Practitioner, Google Cloud Certified Associate Cloud Engineer, Google Cloud Certified Generative AI Leader, a Databricks Certified Generative AI Engineer Associate, and an Oracle Cloud Infrastructure 2024 Generative AI Certified Professional.
I am skilled in data analysis, predictive modelling, sentiment analysis, classification, regression, clustering, and object detection. My strong foundation in Python, JavaScript, and SQL, coupled with experience developing REST APIs, enables me to create robust solutions. I am also well-versed in cloud computing, with expertise in deploying machine learning models on both Google Cloud and AWS.
🚩AREA OF EXPERTISE
-----------------------------------
✔️ LLM Fine-tuning & Deployment
✔️ Generative AI Applications
✔️ Retrieval-Augmented Generation (RAG)
✔️ Machine Learning (ML) and Deep Learning(DL)
✔️ Data Analysis and Visualisation
✔️ Natural Language Processing(NLP)
✔️ Time series forecasting, Anomaly detection
✔️ AI Applications building using open-source models and Hugging Face tools
✔️ GCP & AWS AI Services
✔️ API Development
🚩TECHNICAL SKILLS
--------------------------------------------------------
✔️ Python, JavaScript, SQL
✔️ LangChain | LangGraph | LlamaIndex | Autogen | Swarm | CrewAI | OpenAI GPT-4o | Claude | Gemini | Llama 3
✔️ Pinecone | Qdrant | Chroma | FAISS
✔️ Numpy, Pandas, Jupyter Notebook, Matplotlib, Seaborn, Plotly
✔️ SciKit-Learn, NLTK, BeautifulSoup, Statsmodel
✔️ TensorFlow, Keras, PyTorch, PyTorch Lightning
✔️ OpenCV, Scikit-Image, Pillow, Tesseract
✔️ DNN, CNN, RNN/LSTM, GAN
✔️ Hugging Face Transformers,
✔️ FastAPI, Flask, Streamlit
I believe clear communication is key to success, and I prioritise understanding my clients' needs and vision. I'm excited to apply my skills to new challenges and am confident in making valuable contributions to any team. Thank you for considering my profile, and I look forward to the opportunity to work with you soon.
Steps for completing your project
After purchasing the project, send requirements so Sani can start the project.
Delivery time starts when Sani receives requirements from you.
Sani works on your project following the steps below.
Revisions may occur after the delivery date.
Discovery & Data Assessment
I begin by reviewing your specific use case, such as summarisation or image captioning, and assessing your existing data. I determine if the dataset is properly formatted for Gemini or if it requires transformation into JSONL.
Dataset Preparation & Formatting
I will assist in cleaning, labelling, and formatting your data to meet Google’s high-quality standards for supervised fine-tuning. This includes preparing text, documents, code, images, or audio files for the training pipeline.