L3-Nymeria-8B-exl2

The smartest L3 8B model combined with high-end RP model. What could go wrong.

The idea was to fuse a bit of SimPO's realism with Stheno. It took a few days to come up with a balanced slerp configuration, but I'm more than satisfied with the end result.

Available quants

• 8.0 bpw
• 6.5 bpw
• 5.0 bpw
• 4.25 bpw

Download with git:

git clone --single-branch --branch 6.5 https://huggingface.co/tannedbum/L3-Nymeria-8B-exl2 L3-Nymeria-8B-exl2-6.5

SillyTavern

Text Completion presets

temp 0.9
top_k 30
top_p 0.75
min_p 0.2
rep_pen 1.1
smooth_factor 0.25
smooth_curve 1

Advanced Formatting

Context & Instruct preset by Virt-io

Instruct Mode: Enabled

merge

This is a merge of pre-trained language models created using mergekit.

This model was merged using the slerp merge method.

Models Merged

The following models were included in the merge:

• Sao10K/L3-8B-Stheno-v3.2
• princeton-nlp/Llama-3-Instruct-8B-SimPO

Configuration

The following YAML configuration was used to produce this model:

slices:
  - sources:
      - model: Sao10K/L3-8B-Stheno-v3.2
        layer_range: [0, 32]
      - model: princeton-nlp/Llama-3-Instruct-8B-SimPO
        layer_range: [0, 32]
merge_method: slerp
base_model: Sao10K/L3-8B-Stheno-v3.2
parameters:
  t:
    - filter: self_attn
      value: [0.4, 0.5, 0.6, 0.4, 0.6]
    - filter: mlp
      value: [0.6, 0.5, 0.4, 0.6, 0.4]
    - value: 0.5
dtype: bfloat16

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Original model information:

Model: Sao10K/L3-8B-Stheno-v3.2

Stheno-v3.2-Zeta

Changes compared to v3.1 <br>- Included a mix of SFW and NSFW Storywriting Data, thanks to Gryphe <br>- Included More Instruct / Assistant-Style Data <br>- Further cleaned up Roleplaying Samples from c2 Logs -> A few terrible, really bad samples escaped heavy filtering. Manual pass fixed it. <br>- Hyperparameter tinkering for training, resulting in lower loss levels.

Testing Notes - Compared to v3.1 <br>- Handles SFW / NSFW seperately better. Not as overly excessive with NSFW now. Kinda balanced. <br>- Better at Storywriting / Narration. <br>- Better at Assistant-type Tasks. <br>- Better Multi-Turn Coherency -> Reduced Issues? <br>- Slightly less creative? A worthy tradeoff. Still creative. <br>- Better prompt / instruction adherence.

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