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I will fine tune llm models with a custom dataset
AI, Machine Learning, Deep Learning, Python Expert
Hi! I’m Sandeep Kumar Mishra, and I bring over 6 years of experience in AI, Machine Learning, Deep Learning, Large Language Models and Python. My passion is Python programming, and I’m dedicated to wo...
Level 1
Has met certain performance criteria and shows strong potential in the marketplace.
About this Gig
I'm Sandeep, and I specialize in fine-tuning LLM models to perfectly align with your project's unique requirements. I'll meticulously prepare your dataset to meet LLM's specifications before embarking on the training process.
- Essential Fine-Tuning: Perfect for small projects, this package offers basic LLM model optimization for simple applications. Ideal for startups and individual innovators.
- Advanced Fine-Tuning: Step up with comprehensive fine-tuning, advanced data processing, and performance testing. Suited for businesses aiming to refine their AI applications like e-commerce recommendations or chatbots.
- Elite Fine-Tuning: Our premium package provides top-tier fine-tuning, extensive customization, ongoing support, and post-launch optimization for critical and complex applications.
I can train following LLM Models:
- GPT-3
- GPT-4
- LLAMA-2
- LLAMA-3
- MIXTRAL 7B
- MIXTRAL 8X7B
- BERT
- T5
- ROBERTA
- XLNET
- ALBERT
- ELECTRA
- BART
- ERNIE
- DEBERTA
- MEGATRON-LM
- LONGFORMER
- BLENDERBOT
- OPT
- VICUNA
- XGEN-7B
Looking forward to work with you!
My Portfolio
FAQ
What is fine-tuning in the context of LLMs?
Fine-tuning is the process of taking a pre-trained large language model and training it further on a specific dataset to adapt it for a particular task.
How long does fine-tuning an LLM typically take?
The duration of fine-tuning depends on several factors including the size of the model, the complexity of the task, and the amount of custom data available. It can range from a few hours to several days.
What data is needed for fine-tuning an LLM?
The data required for fine-tuning should be closely related to the tasks the model is expected to perform.
