RichardErkhov
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README.md
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Quantization made by Richard Erkhov.
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[Github](https://github.com/RichardErkhov)
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[Discord](https://discord.gg/pvy7H8DZMG)
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[Request more models](https://github.com/RichardErkhov/quant_request)
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NeuralSynthesis-7B-v0.2 - bnb 8bits
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- Model creator: https://huggingface.co/Kukedlc/
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- Original model: https://huggingface.co/Kukedlc/NeuralSynthesis-7B-v0.2/
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Original model description:
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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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license: apache-2.0
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---
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# NeuralSynthesis-7B-v0.2
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/64d71ab4089bc502ceb44d29/ID4yrGgmKZzqctPPkT4Dp.png)
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NeuralSynthesis-7B-v0.2 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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## 🧩 Configuration
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```yaml
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models:
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- model: Kukedlc/Fasciculus-Arcuatus-7B-slerp
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- model: Gille/StrangeMerges_30-7B-slerp
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- model: automerger/OgnoExperiment27-7B
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- model: Kukedlc/Jupiter-k-7B-slerp
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- model: Kukedlc/Neural-4-QA-7b
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- model: Kukedlc/NeuralSynthesis-7B-v0.1
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merge_method: model_stock
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base_model: Kukedlc/NeuralSynthesis-7B-v0.1
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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 = "Kukedlc/NeuralSynthesis-7B-v0.2"
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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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