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README.md
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license: apache-2.0
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---
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tags:
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- merge
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- mergekit
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- lazymergekit
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- mlabonne/OmniBeagle-7B
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- flemmingmiguel/MBX-7B-v3
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- AiMavenAi/AiMaven-Prometheus
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base_model:
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- mlabonne/OmniBeagle-7B
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- flemmingmiguel/MBX-7B-v3
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- AiMavenAi/AiMaven-Prometheus
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license: apache-2.0
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---
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# NeuralTrix-7B-v1
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NeuralTrix-7B-v1 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [mlabonne/OmniBeagle-7B](https://huggingface.co/mlabonne/OmniBeagle-7B)
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* [flemmingmiguel/MBX-7B-v3](https://huggingface.co/flemmingmiguel/MBX-7B-v3)
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* [AiMavenAi/AiMaven-Prometheus](https://huggingface.co/AiMavenAi/AiMaven-Prometheus)
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It was then trained with DPO using:
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* https://huggingface.co/datasets/jondurbin/truthy-dpo-v0.1
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## 🧩 Configuration
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```yaml
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models:
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- model: mistralai/Mistral-7B-v0.1
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# no parameters necessary for base model
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- model: mlabonne/OmniBeagle-7B
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parameters:
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density: 0.65
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weight: 0.4
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- model: flemmingmiguel/MBX-7B-v3
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parameters:
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density: 0.6
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weight: 0.35
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- model: AiMavenAi/AiMaven-Prometheus
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parameters:
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density: 0.6
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weight: 0.35
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merge_method: dare_ties
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base_model: mistralai/Mistral-7B-v0.1
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parameters:
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int8_mask: true
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dtype: float16
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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 = "CultriX/NeuralTrix-7B-v1"
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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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```
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