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README.md
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- lazymergekit
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#
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models:
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- model: Edgerunners/meta-llama-3-8b-instruct-hf-ortho-baukit-10fail-1000total+ResplendentAI/Aura_Llama3
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- model: Edgerunners/meta-llama-3-8b-instruct-hf-ortho-baukit-10fail-1000total+ResplendentAI/Luna_Llama3
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merge_method: model_stock
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base_model: Edgerunners/meta-llama-3-8b-instruct-hf-ortho-baukit-10fail-1000total
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dtype: float16
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```
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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 = "jeiku/Orthocopter_8B"
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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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license: apache-2.0
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language:
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- en
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# Orthocopter
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/626dfb8786671a29c715f8a9/B1V2QhXSqtBRHT6MW6cCD.png)
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This model is thanks to the hard work of lucyknada with the Edgerunners. Her work produced the following model, which I used as the base:
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https://huggingface.co/Edgerunners/meta-llama-3-8b-instruct-hf-ortho-baukit-10fail-1000total
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I then applied two handwritten datasets over top of this and the results are pretty nice, with no refusals and plenty of personality.
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