Create README.md
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README.md
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---
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license: other
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tags:
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- merge
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- mergekit
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- lazymergekit
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base_model:
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- mlabonne/Meta-Llama-3-120B-Instruct
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- mlabonne/Meta-Llama-3-120B-Instruct
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- mlabonne/Meta-Llama-3-120B-Instruct
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- mlabonne/Meta-Llama-3-120B-Instruct
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- mlabonne/Meta-Llama-3-120B-Instruct
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- mlabonne/Meta-Llama-3-120B-Instruct
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- mlabonne/Meta-Llama-3-120B-Instruct
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- mlabonne/Meta-Llama-3-120B-Instruct
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- mlabonne/Meta-Llama-3-120B-Instruct
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- mlabonne/Meta-Llama-3-120B-Instruct
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- mlabonne/Meta-Llama-3-120B-Instruct
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- mlabonne/Meta-Llama-3-120B-Instruct
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- mlabonne/Meta-Llama-3-120B-Instruct
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---
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/X1tDlFYMMFPNI_YkDXYbE.png)
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# Meta-Llama-3-225B-Instruct
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- This is quantized version of [mlabonne/Meta-Llama-3-225B-Instruct](https://huggingface.co/mlabonne/Meta-Llama-3-225B-Instruct) created using llama.cpp
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Meta-Llama-3-225B-Instruct is a self-merge with [meta-llama/Meta-Llama-3-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct).
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It was inspired by large merges like:
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- [alpindale/goliath-120b](https://huggingface.co/alpindale/goliath-120b)
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- [nsfwthrowitaway69/Venus-120b-v1.0](https://huggingface.co/nsfwthrowitaway69/Venus-120b-v1.0)
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- [cognitivecomputations/MegaDolphin-120b](https://huggingface.co/cognitivecomputations/MegaDolphin-120b)
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- [wolfram/miquliz-120b-v2.0](https://huggingface.co/wolfram/miquliz-120b-v2.0).
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I don't recommend using it as it seems to break quite easily (but feel free to prove me wrong).
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## 🧩 Configuration
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```yaml
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slices:
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- sources:
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- layer_range: [0, 20]
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model: mlabonne/Meta-Llama-3-120B-Instruct
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- sources:
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- layer_range: [10, 30]
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model: mlabonne/Meta-Llama-3-120B-Instruct
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- sources:
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- layer_range: [20, 40]
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model: mlabonne/Meta-Llama-3-120B-Instruct
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- sources:
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- layer_range: [30, 50]
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model: mlabonne/Meta-Llama-3-120B-Instruct
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- sources:
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- layer_range: [40, 60]
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model: mlabonne/Meta-Llama-3-120B-Instruct
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- sources:
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- layer_range: [50, 70]
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model: mlabonne/Meta-Llama-3-120B-Instruct
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- sources:
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- layer_range: [60, 80]
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model: mlabonne/Meta-Llama-3-120B-Instruct
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- sources:
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- layer_range: [70, 90]
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model: mlabonne/Meta-Llama-3-120B-Instruct
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- sources:
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- layer_range: [80, 100]
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model: mlabonne/Meta-Llama-3-120B-Instruct
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- sources:
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- layer_range: [90, 110]
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model: mlabonne/Meta-Llama-3-120B-Instruct
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- sources:
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- layer_range: [100, 120]
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model: mlabonne/Meta-Llama-3-120B-Instruct
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- sources:
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- layer_range: [110, 130]
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model: mlabonne/Meta-Llama-3-120B-Instruct
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- sources:
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- layer_range: [120, 140]
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model: mlabonne/Meta-Llama-3-120B-Instruct
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merge_method: passthrough
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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 = "mlabonne/Meta-Llama-3-220B-Instruct"
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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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