LLM-3D Print: Large Language Models To Monitor and Control 3D Printing
Aug 26, 2024 · The LLM evaluates print quality by analyzing images captured after each layer or print segment, identifying failure modes and querying the printer for relevant parameters. It then generates and executes a corrective action plan.
LLM-3D Print: Large Language Models To Monitor and Control 3D Printing
Aug 26, 2024 · To address these challenges, we present a process monitoring and control framework that leverages pre-trained Large Language Models (LLMs) alongside 3D printers to detect and address printing defects.
PrinterChat - Google Sites
The LLM evaluates print quality by analyzing images captured after each layer or print segment, identifying failure modes and querying the printer for relevant parameters. It then generates and...
LLM-Powered 3D Model Generation System for 3D Printing
Build Great AI developed a prototype application that leverages multiple LLM models to generate 3D printable models from text descriptions. The system uses various models including LLaMA 3.1, GPT-4, and Claude 3.5 to generate OpenSCAD code, which is …
LLM-3D Print: Large Language Models To Monitor and Control 3D Printing
Aug 26, 2024 · To address these challenges, we present a process monitoring and control framework that leverages pre-trained Large Language Models (LLMs) alongside 3D printers to detect and address printing...
Models are repeating text several times? : r/LocalLLaMA - Reddit
May 21, 2023 · local_llm = HuggingFacePipeline(pipeline=pipe) text = 'What is the capital of france?' input_ids = tokenizer.encode(text, return_tensors="pt").gpu() print(input_ids)
Issue: How to print the complete prompt that chain used #6628 - GitHub
Jun 22, 2023 · This will cause LangChain to give detailed output for all the operations in the chain/agent, but that output will include the prompt sent to the LLM.
How return LLMChain.run() stream data?? it did not store ... - GitHub
Aug 10, 2023 · Based on the context provided, it seems you want to return the streaming data from LLMChain.run() instead of printing it. This can be achieved by using Python's built-in yield keyword, which allows a function to return a stream of data, one item at a time.
How to Get Structured Output from LLMs Applications Using
Aug 19, 2024 · In this article, you will learn how to ensure consistent output structures from your LLM applications, specifically in JSON format, by using two open-source libraries: Pydantic and Instructor.
Every Way To Get Structured Output From LLMs
Nov 26, 2024 · The best way to get an LLM to return structured data is to craft a prompt designed to return data matching your specific schema. To do that, you need to see the prompt actually getting sent to ChatGPT, and
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