This quant was made using exllamav2-0.1.7 with default dataset. I used a slightly modified quantization script to force use of highest bpw methods for all layers in the model (which is usually "1:8b_128g s4") to ensure max quality.
I also added a small fix in config file to set max default context at 128k as original Mistral-Nemo should have.
I tested this quant shortly in some random RPs (including ones over 8k context) and it seems to work fine.
Uses Mistral format.
This model is the miniature version of
alpindale/magnum-72b-v1, a second entry in a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet and Opus. This model is fine-tuned on top of
Mistral-Nemo-Base-2407.
A new general purpose instruction dataset by kalomaze was added to the training mix for better coherence and general alignment. We are working on improving our dataset and training procedures, so expect new versions to come out soon.
Model has been Instruct tuned with the Mistral formatting. A typical input would look like this:
1"""[INST] Hi there! [/INST]Nice to meet you!</s>[INST] Can I ask a question? [/INST]
2"""
...
