Slide 13
Slide 13 text
Vector DB
Query
LLM
Response
Retrieved
contexts
Embedding
model
llms = ["gpt-3.5-turbo",
"gpt-4",
"meta-llama/Llama-2-7b",
"meta-llama/Llama-2-13b",
"meta-llama/Llama-2-70b",
"codellama/CodeLlama-34b-Instruct-hf",
"mistralai/Mistral-7B-Instruct-v0.1"]
embedding_model_names =
["thenlper/gte-base",
"thenlper/gte-large",
"BAAI/bge-large-en",
"text-embedding-ada-002"]
chunk_sizes = [100, 300, 500, 700, 900]
num_chunks_list = [1, 3, 5, 7, 9]
Experiments