---
base_model:
- OmnicromsBrain/ToppyCox-10.7b
- OmnicromsBrain/EverythingBagel-10.7b
tags:
- merge
- mergekit
- lazymergekit
- OmnicromsBrain/ToppyCox-10.7b
- OmnicromsBrain/EverythingBagel-10.7b
---

![image/png](https://cdn-uploads.huggingface.co/production/uploads/65c70c9e21d80a923d664563/sM8repDdiFzeJ6M0twE88.png)

# Eros_Scribe-10.7b-v3


This model was created for the purpose of writing NSFW Prose but it's also very good at RP.

Versions 1 and 2 were the most verbose models I'd ever merged but they had lost most of their NSFW MoJo.
I think I finally got the mix right as v3 returns some of the most NSFW I've seen...


Over a dozen models and at least 25 dataset were involved in this merge. Eros_Scribe-10.7b-v3 is a merge of the following models:

## OmnicromsBrain/EverythingBagel-DPO-7B

### jondurbin/bagel-dpo-7b-v0.5

### SanjiWatsuki/Silicon-Maid-7B

chargoddard/loyal-piano-m7

NeverSleep/Noromaid-7b-v0.2

athirdpath/NSFW_DPO_vmgb-7b

xDAN-AI/xDAN-L1-Chat-RL-v1

## OmnicromsBrain/ToppyCox-7B

### N8Programs/Coxcomb

### Undi95/Toppy-M-7B

openchat/openchat_3.5

NousResearch/Nous-Capybara-7B-V1.9

HuggingFaceH4/zephyr-7b-beta

Undi95/zephyr-7b-beta-pippa-sharegpt

Undi95/Nous-Capybara-7B-V1.9-120-Days

Undi95/openchat_3.5-LimaRP-13B

lemonilia/AshhLimaRP-Mistral-7B

mistralai/Mistral-7B-v0.1


## ⚡ Quantized Models

Special thanks to **MRadermacher** for the **static** and **imatrix** quantized models

**.GGUF** https://huggingface.co/mradermacher/Eros_Scribe-10.7b-v3-GGUF

**IMatrix** https://huggingface.co/mradermacher/Eros_Scribe-10.7b-v3-i1-GGUF



## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "OmnicromsBrain/Eros_Scribe-10.7b-v3"
messages = [{"role": "user", "content": "What is a large language model?"}]

tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
```