---
license: apache-2.0
datasets:
- anthracite-org/kalo-opus-instruct-22k-no-refusal
- Nopm/Opus_WritingStruct
- Gryphe/Sonnet3.5-SlimOrcaDedupCleaned
- Gryphe/Sonnet3.5-Charcard-Roleplay
- Gryphe/ChatGPT-4o-Writing-Prompts
- Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
- Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
- nothingiisreal/Reddit-Dirty-And-WritingPrompts
- allura-org/Celeste-1.x-data-mixture
- allura-org/shortstories_synthlabels
base_model:
- Qwen/Qwen2.5-14B
---

[This is the EXL2 8bpw version of this model. For the original model, go here.](https://huggingface.co./EVA-UNIT-01/EVA-Qwen2.5-14B-v0.1)
<br>
[For the 6bpw version, go here](https://huggingface.co./Statuo/EVA-UNIT-01_EVA-Qwen2.5-14B-v0.1-EXL2-6bpw)
<br>
[For the 4bpw version, go here](https://huggingface.co./Statuo/EVA-UNIT-01_EVA-Qwen2.5-14B-v0.1-EXL2-4bpw)
<br>

**EVA Qwen2.5 14B 0.1**
  
<p>
  A RP/storywriting specialist model, full-parameter finetune of Qwen2.5-7B on mixture of synthetic and natural data.<br>
  It uses Celeste 70B 0.1 data mixture, greatly expanding it to improve versatility, creativity and "flavor" of the resulting model.<br>
</p>

<p>
  <b>Version 0.1 notes:</b><br> Dataset was deduped and cleaned from version 0.0, sequence length was also increased. Resulting model seems to be stabler, and 0.0 problems with handling short inputs and min_p sampling seem to be gone.<br>
  This version seems to be more or less optimal for the current data and available compute. 
</p>

<p>Note: using quantized KV cache with Qwen2.5 <b>is not recommended</b> and can lead to degraded output quality. On the other hand, Qwen's KV cache is already light enough, so using f16 for it shouldn't be problematic.</p>

<p>
  <p>Prompt format is ChatML.</p><br>
  <h3>Recommended sampler values:</h3>
  <ul>
  <li>Temperature: 1</li>
  <li>Typical-P: 0.9</li>
  <li>Min-P: 0.05</li>
  <li>Top-A: 0.2</li>
  <li>Repetition Penalty: 1.03</li>
  </ul>
  
  <h3>Recommended SillyTavern presets (via CalamitousFelicitousness):</h3>

  - [Context](https://huggingface.co./EVA-UNIT-01/EVA-Yi-1.5-9B-32K-V1/blob/main/%5BChatML%5D%20Roleplay-v1.9%20Context.json)
  - [Instruct and System Prompt](https://huggingface.co./EVA-UNIT-01/EVA-Yi-1.5-9B-32K-V1/blob/main/%5BChatML%5D%20Roleplay-v1.9%20Instruct.json)
</p>

<p>
  <br>
  <h3>
    Training data:
  </h3>
    <ul>
      <li>Celeste 70B 0.1 data mixture minus Opus Instruct subset. See that model's <a href=https://huggingface.co./nothingiisreal/L3.1-70B-Celeste-V0.1-BF16>card</a> for details.</li>
      <li>Kalomaze's Opus_Instruct_25k dataset, filtered for refusals.</li>
      <li>A subset (1k rows) of ChatGPT-4o-WritingPrompts by Gryphe</li>
      <li>A subset (2k rows) of Sonnet3.5-Charcards-Roleplay by Gryphe</li>
      <li>A cleaned subset (~3k rows) of shortstories_synthlabels by Auri</li>
      <li>Synthstruct and SynthRP datasets by Epiculous</li>
    </ul>
  <h3>
     Training time and hardware:
  </h3>
      <ul><li>3 days on 4xA6000</li></ul><br>
</p>
  Model was trained by Kearm and Auri.
  <h4>Special thanks:</h4><ul>
  <li>to Gryphe, Lemmy, Kalomaze, Nopm and Epiculous for the data</li>
  <li>to Alpindale for helping with FFT config for Qwen2.5</li>
  <li>and to Allura-org for support and feedback on EVA models.</li></ul>