---
license: other
language:
- en
pipeline_tag: text-generation
inference: false
tags:
- transformers
- gguf
- imatrix
- Eros_Scribe-7b
---
Quantizations of https://huggingface.co/OmnicromsBrain/Eros_Scribe-7b


### Open source inference clients/UIs
* [llama.cpp](https://github.com/ggerganov/llama.cpp)
* [KoboldCPP](https://github.com/LostRuins/koboldcpp)
* [ollama](https://github.com/ollama/ollama)
* [text-generation-webui](https://github.com/oobabooga/text-generation-webui)
* [jan](https://github.com/janhq/jan)
* [GPT4All](https://github.com/nomic-ai/gpt4all)

### Closed source inference clients/UIs
* [LM Studio](https://lmstudio.ai/)
* [Backyard AI](https://backyard.ai/)
* More will be added...
---

# From original readme

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

Over a dozen models and at least 25 dataset were involved in this merge.
Eros_Scribe-7b is a merge of the following models:

* [OmnicromsBrain/EverythingBagel-DPO-7B](https://huggingface.co/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](https://huggingface.co/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

  
BTW the name was suggested by Mistral 8x7b instruct


## 🧩 Configuration

```yaml
slices:
  - sources:
      - model: OmnicromsBrain/EverythingBagel-DPO-7B
        layer_range: [0, 32]
      - model: OmnicromsBrain/ToppyCox-7B
        layer_range: [0, 32]
merge_method: slerp
base_model: OmnicromsBrain/EverythingBagel-DPO-7B
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
dtype: bfloat16
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "OmnicromsBrain/Eros_Scribe-7b"
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"])
```