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bartowski 
posted an update Sep 6
Post
34932
Reposting from twitter:

Just so you all know, I'll be on vacation for the following two weeks and away from home! I'm hoping to get on at least once a day to load up some quants, but I won't be as bleeding edge and on the ball :) feel free to shoot me a message if you see one I should make!

In the meantime if you need something bleeding edge make sure to check out @MaziyarPanahi or @bullerwins who both put out great work!

Have a great vacation, bro! 😎

Congratulations on your relevant contributions to the open source community!
I have been using your quantized models in the development of the Samantha Interface Assistant (github.com/controlecidadao/samantha_ia). Have a great vacation!

Hope you have a great vacation! Once you're back and looking for a model to quant, hope you'll consider: meta-llama/Llama-3.2-11B-Vision-Instruct to a Q8_0.gguf.

hi do you can fine tun lama3 70 B on this med data and how its will be cost ?

  1. MIMIC-III (Medical Information Mart for Intensive Care):
    ◦ Description: A database of medical records from intensive care units.
    ◦ Access: PhysioNet
  2. PubMedQA:
    ◦ Description: A dataset of medical questions and answers based on articles from PubMed.
    ◦ Access: Hugging Face Datasets
  3. MedNLI (Medical Natural Language Inference):
    ◦ Description: A dataset for analyzing logical inference in medical texts.
    ◦ Access: PhysioNet
  4. BioASQ:
    ◦ Description: A dataset for the task of automatic question answering based on biomedical literature.
    ◦ Access: BioASQ
  5. SQuAD v2 (Stanford Question Answering Dataset) with medical questions:
    ◦ Description: A standard set of questions and answers, extended with medical questions.
    ◦ Access: Hugging Face Datasets
  6. Clinical STS (Clinical Semantic Textual Similarity):
    ◦ Description: Dataset for the task of semantic textual similarity in medical texts.
    ◦ Access: Hugging Face Datasets
  7. CHEXPERT:
    ◦ Description: Dataset of chest x-ray images with medical labels for training.
    ◦ Access: Stanford ML Group