Figuring out general specs for running LLM models – Deep-learning
The Problem: I have a machine learning model with a certain number of parameters. How … Read more
The Problem: I have a machine learning model with a certain number of parameters. How … Read more
Quick Fix: Use the where clause when querying to limit results based on metadata. results … Read more
The Problem: You are using llama_index with a custom LLM, the Open Assistant Pythia model, … Read more
The Solutions: Solution 1: Use a model with instruction tuning and logits processor To resolve … Read more
The Problem: Given a Chroma Vector Store with files belonging to different users, devise a … Read more
Quick Fix: To resolve the issue with ChatGPT via Pydantic, employ a try/except block, delete … Read more
Quick Fix: To load the index using LangChain and perform a query, you can use … Read more
Quick Fix: To obtain embeddings using GPT-like LLMs, utilize a transformer encoder model rather than … Read more
Quick Fix: Change from llama_index.llms import CustomLLM, CompletionResponse, LLMMetadata To this from llama_index.llms.custom import CustomLLM … Read more
Quick Fix: Both LangChain and LlamaIndex can be used with large language models, but LangChain … Read more
Quick Fix: The provided code can be enhanced to extract the page number from the … Read more
Quick Fix: Instruction tuning is a specialized form of fine-tuning where the model is optimized … Read more
Quick Fix: To retrieve source_documents and score from ConversationalRetrievalChain, ensure you provide return_source_documents as True … Read more
Quick Fix: Upgrade the peft package using pip install –upgrade peft. This should resolve the … Read more
Quick Fix: The error might be due to embeddings variable. Verify the parameters of LlamaCppEmbeddings … Read more