---
base_model:
- meta-llama/Llama-3.1-70B
- EVA-UNIT-01/LLaMA-EVA-3.33-70B-v0.0
- EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.0
library_name: transformers
license: other
license_name: eva-llama3.3
tags:
- mergekit
- merge
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
- cognitivecomputations/dolphin-2.9.3
---

# EVA LLaMA 3.33 70B v0.1
  A RP/storywriting specialist model, full-parameter finetune of Llama-3.3-70B-Instruct 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>
  This model was built with Llama by Meta.

## Version notes for v0.1

  DELLA linear merge of v0.0 with an unreleased checkpoint from a different run. Reduced overfitting, better long context comprehension and recall, less repetition, more stability.

  <p>
  <p>Prompt format is Llama3.</p><br>
  <h3>Recommended sampler values:</h3>
  <ul>
  <li>Temperature: 1</li>
  <li>Min-P: 0.05</li>
  <li>Repetition Penalty: 1.03</li>
  </ul>
  
  <h3>Recommended SillyTavern preset (via Virt-io):</h3>
    <ul><li><a href="https://huggingface.co/EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.0/blob/main/EV01-llama.json">Master import</a></li></ul>
  </p>

  <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>Synthstruct and SynthRP datasets by Epiculous</li>
      <li>A subset from Dolphin-2.9.3, including filtered version of not_samantha and a small subset of systemchat.</li>
    </ul>

  <p>Model was created by Kearm, Auri and Cahvay.</p>
  <h4>Special thanks:</h4><ul>
  <li>to Cahvay for his work on dataset filtering.</li>
  <li>to Gryphe, Lemmy, Kalomaze, Nopm, Epiculous and CognitiveComputations for the data</li>
  <li>and to Allura-org for support, feedback, beta-testing and doing quality control of EVA models.</li></ul>

  <h3>Licensing</h3>
  <p>Llama-3.3-70B-Instruct by Meta is licensed under <a href=https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct/blob/main/LICENSE>Llama 3.3 Community License Agreement (further referred as L3.3 license)</a> and is a subject to <a href=https://www.llama.com/llama3_3/use-policy>Acceptable Use Policy for Llama Materials</a>.<br>
  This derivative is free for personal, research and commercial use on terms of L3.3 license with one extra clause: <br>
  - Infermatic Inc and any of its employees or paid associates cannot utilize, distribute, download, or otherwise make use of EVA models for any purpose.</p>


---
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).

## Merge Details
### Merge Method

This model was merged using the linear [DELLA](https://arxiv.org/abs/2406.11617) merge method using [meta-llama/Llama-3.1-70B](https://huggingface.co/meta-llama/Llama-3.1-70B) as a base.

### Models Merged

The following models were included in the merge:
* [EVA-UNIT-01/LLaMA-EVA-3.33-70B-v0.0](https://huggingface.co/EVA-UNIT-01/LLaMA-EVA-3.33-70B-v0.0)
* [EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.0](https://huggingface.co/EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.0)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
models:
  - model: EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.0
    parameters:
      density: 0.6
      weight: 0.3
      lambda: 1.1
      epsilon: 0.35
  - model: EVA-UNIT-01/LLaMA-EVA-3.33-70B-v0.0
    parameters:
      density: 0.45
      weight: 0.7
      lambda: 1.1
      epsilon: 0.4
merge_method: della_linear
base_model: meta-llama/Llama-3.1-70B
parameters:
  normalize: true
  int8_mask: true
dtype: bfloat16
```