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README.md

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+
+---
+
+base_model:
+- akjindal53244/Llama-3.1-Storm-8B
+- Sao10K/L3.1-8B-Niitama-v1.1
+- v000000/L3.1-Niitorm-8B-t0.0001
+library_name: transformers
+tags:
+- merge
+- llama
+- dpo
+datasets:
+- jondurbin/gutenberg-dpo-v0.1
+
+---
+
+[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory)
+
+
+# QuantFactory/L3.1-Niitorm-8B-DPO-t0.0001-GGUF
+This is quantized version of [v000000/L3.1-Niitorm-8B-DPO-t0.0001](https://huggingface.co/v000000/L3.1-Niitorm-8B-DPO-t0.0001) created using llama.cpp
+
+# Original Model Card
+
+
+# Llama-3.1-Niitorm-8B-DPO
+
+* *DPO Trained, Llama3.1-8B.*
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/64f74b6e6389380c77562762/QeNjtwolNpxUmpo9NL7VI.png)
+
+<b>New: DPO'd Gutenberg Version (full epoch training).</b>
+
+RP model, Niitama 1.1 as a base, nearswapped with one of the smartest 3.1 models "Storm", then DPO'd, mostly abliterated.
+
+Essentially, it's an improved Niitama 1.1
+
+-------------------------------------------------------------------------------
+
+*Gutenberg DPO creates more human-like prose/story writing and greately lessen synthetic feeling outputs.*
+
+-------------------------------------------------------------------------------
+
+# *llama.cpp:*
+
+# thank you, mradermacher (GGUF)
+
+* [GGUF static](https://huggingface.co/mradermacher/L3.1-Niitorm-8B-DPO-t0.0001-GGUF)
+
+* [GGUF Imatrix](https://huggingface.co/mradermacher/L3.1-Niitorm-8B-DPO-t0.0001-i1-GGUF)
+
+# v0 (GGUF)
+
+* [GGUF Imatrix](https://huggingface.co/v000000/L3.1-Niitorm-8B-DPO-t0.0001-GGUFs-IMATRIX) *-only q8, q6 k, q5 k s, q4 k s, iq4 x s*
+
+
+## Finetune and merge
+
+This is a merge and finetune of pre-trained language models.
+
+*Resultant merge finetuned* on [jondurbin/gutenberg-dpo-v0.1](https://huggingface.co/datasets/jondurbin/gutenberg-dpo-v0.1) for 1 epoch, 1.5e-5 learning rate, on Nvidia A100.
+
+## Merge Details
+### Merge Method
+
+This model was merged using the <b>NEARSWAP t0.0001</b> merge algorithm.
+
+### Models Merged
+
+The following models were included in the merge:
+* Base Model: [Sao10K/L3.1-8B-Niitama-v1.1](https://huggingface.co/Sao10K/L3.1-8B-Niitama-v1.1) + [grimjim/Llama-3-Instruct-abliteration-LoRA-8B](https://huggingface.co/grimjim/Llama-3-Instruct-abliteration-LoRA-8B)
+* [akjindal53244/Llama-3.1-Storm-8B](https://huggingface.co/akjindal53244/Llama-3.1-Storm-8B)
+
+### Configuration
+
+The following YAML configuration was used to produce this model:
+
+```yaml
+slices:
+  - sources:
+      - model: Sao10K/L3.1-8B-Niitama-v1.1+grimjim/Llama-3-Instruct-abliteration-LoRA-8B
+        layer_range: [0, 32]
+      - model: akjindal53244/Llama-3.1-Storm-8B
+        layer_range: [0, 32]
+merge_method: nearswap
+base_model: Sao10K/L3.1-8B-Niitama-v1.1+grimjim/Llama-3-Instruct-abliteration-LoRA-8B
+parameters:
+  t:
+    - value: 0.0001
+dtype: float16
+
+# Then, DPO Finetune
+# [jondurbin/gutenberg-dpo-v0.1](https://huggingface.co/datasets/jondurbin/gutenberg-dpo-v0.1)
+
+```
+
+### DPO Notes
+
+*I used a higher learning rate and full dataset when training compared to my "L3.1-Celestial-Stone-2x8B-DPO". This caused lower loss and better adaption to the chosen style.*
+
+-------------------------------------------------------------------------------
+
+# Prompt Template:
+```bash
+<|begin_of_text|><|start_header_id|>system<|end_header_id|>
+
+{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>
+
+{input}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
+
+{output}<|eot_id|>
+
+```
+
+Credit to Alchemonaut.
+
+Credit to Sao10K.
+
+Credit to Grimjim.
+
+Credit to mlabonne.
+
+Credit to jondurbin.
+
+Credit to woofwolfy.