experiment_2_8b-iMat-GGUF

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PROUDLY PRESENTS         

experiment_2_8b-iMat-GGUF

<b>Quantization Notes: Quantized from 3500 checkpoint. Use repetition penalty (--repeat-penalty on llama.cpp) of ~1.15 with Q6_K and lower and ~1.18 with IQ3_M and lower for best results. </b>

Quantized from fp16 with love.

• Weighted quantizations were created using fp16 GGUF and groups_merged-enhancedV2-TurboMini.txt in 189 chunks and n_ctx=512
• This method of calculating the importance matrix showed improvements in some areas for Mistral 7b and Llama3 8b models, see above post for details
• The enhancedv2-turbomini file appends snippets from turboderp's calibration data to the standard groups_merged.txt file

For a brief rundown of iMatrix quant performance please see this PR

<b>All quants are verified working prior to uploading to repo for your safety and convenience. </b>

Original model card here and below

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experiment_2_8b-fp16

Another experimental train w/ unsloth. This time, roughly 0.6 epochs of the cleaned c2-logs. My metaparams are probably bad, since the loss-value was super weird at the end. Also uploaded another version in the checkpoint-3500-branch that may mitigate some of that.