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We need to know how much resource it is used and where it saves the downloaded model if it is kept locally! Does it work offline? Anyway, thanks for the good content. 🌹🌹🌹
In llama.cpp there is no executable filed named as quantize . So when we run this code : for m in methods: qtype = f"{quantized_path}/{m.upper()}.gguf" os.system("./llama.cpp/quantize "+quantized_path+"/FP16.gguf "+qtype+" "+m) Nothing happens and the Q4_K_M.gguf file is not being created .. Any solutions ???????????
nice to see all the crewai examples, thanks. One thing that I like to see is a breakdown of the memory vs context and what exactly do agents store in the context. If have an agent that pulls content from a database, so I pass a page_id to the inputs dict. When the agent finishes, it's extracted a document, but where is that stored, how is it properly referenced and accessed by agents further downstream? Do I specify a key name in the expected_output? ie., store the retrieved document in the context with the key 'database_page'...or something like that? The other frustrating thing is that all the crewai RAG tools point to file paths or URLs etc. So you can't just point to a chunk in context, you have to write out the task output to file and then instantiate the tool... what are your thoughts on the blackbox nature of the context and memory?
ps. is it possible when creating word docs to specify any formatting? Basic things like specifying fonts and adjusting typography or even applying a template. I've been using markdown for everything because its so portable, but it would be nice at the end if there was a straightforward way to dump the crew results into a docx file and make it look nice. Cheers!
build a application in such way that the user upload video in that video x person is facing some fungal disease imagine Gemini Ilm is doctor the Gemini modal want to give some medicine to cure that disease .. please upload this project tomorrow sir😂😂