NLP Model developement
Budget: $50 – $0 CAD
Our project focuses on developing a machine learning model utilizing a confidential dataset. We aim to interact with this model to retrieve specific statuses from our database. Given our offline environment, we will provide the hired individual with access to an isolated virtual machine for development.
Usage Methods:
We offer two distinct methods of use for this system. The first method involves direct integration with the model as described below. The second method leverages LORA, where we have trained our model with our datasets to fine-tune its performance.
Planned Components:
- Data Storage:
We intend to use ChromaDB for storing datasets and documents, as it supports internal local hosting.
- Embedding Model:
We plan to implement the [BAAI/bge-large-en-v1.5](https://huggingface.co/BAAI/bge-large-en-v1.5?utm_source=chatgpt.com) model, which transforms text into 1024-dimensional vectors, facilitating tasks like retrieval and semantic search.
- Interactive Model:
We are considering the [Llama 3.2 1B](https://huggingface.co/meta-llama/Llama-3.2-1B?utm_source=chatgpt.com) model for future interactive capabilities. This lightweight, multilingual model is optimized for tasks such as personal information management and knowledge retrieval, making it suitable for deployment on edge devices.
Usage Methods:
We offer two distinct methods of use for this system. The first method involves direct integration with the model as described below. The second method leverages LORA, where we have trained our model with our datasets to fine-tune its performance.
Planned Components:
- Data Storage:
We intend to use ChromaDB for storing datasets and documents, as it supports internal local hosting.
- Embedding Model:
We plan to implement the [BAAI/bge-large-en-v1.5](https://huggingface.co/BAAI/bge-large-en-v1.5?utm_source=chatgpt.com) model, which transforms text into 1024-dimensional vectors, facilitating tasks like retrieval and semantic search.
- Interactive Model:
We are considering the [Llama 3.2 1B](https://huggingface.co/meta-llama/Llama-3.2-1B?utm_source=chatgpt.com) model for future interactive capabilities. This lightweight, multilingual model is optimized for tasks such as personal information management and knowledge retrieval, making it suitable for deployment on edge devices.