GenAI, LLM and OpenAI/Hugging Face development
Budget: $50 – $0 USD
Need an engineer who is well versed using OpenAI And hugging face API to build fine tuned models with proprietary data.
1. Preprocess the regulations: Clean and preprocess the text to remove any unnecessary formatting or characters, and possibly break the regulations into smaller sections to facilitate processing.
2. Access the LLM: Use an API or SDK provided by the LLM provider (e.g., OpenAI and BLOOM) to interact with the model.
3. Load the regulations: Load the CMS regulations into your program or script, either by reading the text file or querying the database or cloud storage service.
4. Interact with the LLM: Pass relevant sections or text from the regulations along with your formulated questions or prompts to the LLM using the API or SDK.
5. Process the output: Collect the LLM's output, analyze it, and extract the desired rules with context.
We want an MVP of a claim running against the regulations to see if it is well formed. If it rejects we want it to produce reasons.
1. Preprocess the regulations: Clean and preprocess the text to remove any unnecessary formatting or characters, and possibly break the regulations into smaller sections to facilitate processing.
2. Access the LLM: Use an API or SDK provided by the LLM provider (e.g., OpenAI and BLOOM) to interact with the model.
3. Load the regulations: Load the CMS regulations into your program or script, either by reading the text file or querying the database or cloud storage service.
4. Interact with the LLM: Pass relevant sections or text from the regulations along with your formulated questions or prompts to the LLM using the API or SDK.
5. Process the output: Collect the LLM's output, analyze it, and extract the desired rules with context.
We want an MVP of a claim running against the regulations to see if it is well formed. If it rejects we want it to produce reasons.