Original model: https://huggingface.co/jondurbin/bagel-8b-v1.0 All quants made using imatrix option with dataset provided by Kalomaze here If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run: You can either specify a new local-dir (bagel-8b-v1.0-Q8_0) or download them all in place (./) A great write up with charts showing various performances is provided by Artefact2 here The first thing to figure out is how big a model you can run. To do this, you’ll need to figure out how much RAM and/or VRAM you have. If you want your model running as FAST as possible, you’ll want to fit the whole thing on your GPU’s VRAM. Aim for a quant with a file size 1-2GB smaller than your GPU’s total VRAM. If you want the absolute maximum quality, add both your system RAM and your GPU’s VRAM together, then similarly grab a quant with a file size 1-2GB Smaller than that total. Next, you’ll need to decide if you want to use an ‘I-quant’ or a ‘K-quant’. If you don’t want to think too much, grab one of the K-quants. These are in format ‘QXKX’, like Q5KM. If you want to get more into the weeds, you can check out this extremely…
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Автор: bartowski
Теги: gguf, llama-3, bagel, endpoints_compatible, conversational
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Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
