105 lines
2.8 KiB
Markdown
105 lines
2.8 KiB
Markdown
---
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license: other
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language:
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- en
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pipeline_tag: text-generation
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inference: false
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tags:
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- transformers
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- gguf
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- imatrix
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- Eros_Scribe-7b
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---
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Quantizations of https://huggingface.co/OmnicromsBrain/Eros_Scribe-7b
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### Open source inference clients/UIs
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* [llama.cpp](https://github.com/ggerganov/llama.cpp)
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* [KoboldCPP](https://github.com/LostRuins/koboldcpp)
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* [ollama](https://github.com/ollama/ollama)
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* [text-generation-webui](https://github.com/oobabooga/text-generation-webui)
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* [jan](https://github.com/janhq/jan)
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* [GPT4All](https://github.com/nomic-ai/gpt4all)
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### Closed source inference clients/UIs
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* [LM Studio](https://lmstudio.ai/)
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* [Backyard AI](https://backyard.ai/)
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* More will be added...
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---
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# From original readme
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This model was created for the purpose of writing **NSFW Prose** but it's also very good at **RP**.
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Over a dozen models and at least 25 dataset were involved in this merge.
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Eros_Scribe-7b is a merge of the following models:
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* [OmnicromsBrain/EverythingBagel-DPO-7B](https://huggingface.co/OmnicromsBrain/EverythingBagel-DPO-7B)
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* jondurbin/bagel-dpo-7b-v0.5
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* SanjiWatsuki/Silicon-Maid-7B
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* chargoddard/loyal-piano-m7
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* NeverSleep/Noromaid-7b-v0.2
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* athirdpath/NSFW_DPO_vmgb-7b
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* xDAN-AI/xDAN-L1-Chat-RL-v1
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* [OmnicromsBrain/ToppyCox-7B](https://huggingface.co/OmnicromsBrain/ToppyCox-7B)
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* N8Programs/Coxcomb
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* Undi95/Toppy-M-7B
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* openchat/openchat_3.5
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* NousResearch/Nous-Capybara-7B-V1.9
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* HuggingFaceH4/zephyr-7b-beta
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* Undi95/zephyr-7b-beta-pippa-sharegpt
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* Undi95/Nous-Capybara-7B-V1.9-120-Days
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* Undi95/openchat_3.5-LimaRP-13B
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* lemonilia/AshhLimaRP-Mistral-7B
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* mistralai/Mistral-7B-v0.1
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BTW the name was suggested by Mistral 8x7b instruct
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## 🧩 Configuration
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```yaml
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slices:
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- sources:
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- model: OmnicromsBrain/EverythingBagel-DPO-7B
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layer_range: [0, 32]
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- model: OmnicromsBrain/ToppyCox-7B
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layer_range: [0, 32]
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merge_method: slerp
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base_model: OmnicromsBrain/EverythingBagel-DPO-7B
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parameters:
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t:
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- filter: self_attn
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value: [0, 0.5, 0.3, 0.7, 1]
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- filter: mlp
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value: [1, 0.5, 0.7, 0.3, 0]
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- value: 0.5
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dtype: bfloat16
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```
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## 💻 Usage
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```python
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!pip install -qU transformers accelerate
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from transformers import AutoTokenizer
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import transformers
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import torch
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model = "OmnicromsBrain/Eros_Scribe-7b"
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messages = [{"role": "user", "content": "What is a large language model?"}]
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tokenizer = AutoTokenizer.from_pretrained(model)
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prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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pipeline = transformers.pipeline(
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"text-generation",
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model=model,
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torch_dtype=torch.float16,
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device_map="auto",
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)
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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print(outputs[0]["generated_text"])
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``` |