MDNA Plus (MD&A Plus)
Manager's Discussion and Analysis generator. Trained on data set refined from all (public domain by definition) [SEC EDGAR] (https://www.sec.gov/edgar/search/) quarterly and annual report filings before May 2023 where the company's stock price appreciated in the period from 7 days prior to 7 days after the report filing.
Batches of data were then separated into prompt/completion pairs with the prompts generated by Llama3.2:3b. LoRA executed by MLX-LM.
DISCLAIMER
THIS MODEL WAS CREATED FOR EDUCATIONAL PURPOSES. USERS TAKE FULL RESPONSIBILITY FOR THE ACCURACY OF GENERATIONS IF SHARED OR UTILIZED.
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Model size
8B params
Tensor type
BF16
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Hardware compatibility
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# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("maxhirez/mdnaPlus") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True)