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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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- NousResearch/Meta-Llama-3-8B |
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base_model: |
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- NousResearch/Meta-Llama-3-8B |
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- NousResearch/Meta-Llama-3-8B |
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- NousResearch/Meta-Llama-3-8B |
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- NousResearch/Meta-Llama-3-8B |
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- NousResearch/Meta-Llama-3-8B |
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- NousResearch/Meta-Llama-3-8B |
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- NousResearch/Meta-Llama-3-8B |
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- NousResearch/Meta-Llama-3-8B |
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- NousResearch/Meta-Llama-3-8B |
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- NousResearch/Meta-Llama-3-8B |
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- NousResearch/Meta-Llama-3-8B |
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- NousResearch/Meta-Llama-3-8B |
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- NousResearch/Meta-Llama-3-8B |
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- NousResearch/Meta-Llama-3-8B |
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- NousResearch/Meta-Llama-3-8B |
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- NousResearch/Meta-Llama-3-8B |
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--- |
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# llama-3-8b-slow-DUS-layer1-method2 |
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llama-3-8b-slow-DUS-layer1-method2 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): |
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* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B) |
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* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B) |
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* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B) |
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* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B) |
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* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B) |
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* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B) |
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* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B) |
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* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B) |
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* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B) |
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* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B) |
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* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B) |
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* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B) |
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* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B) |
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* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B) |
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* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B) |
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* [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B) |
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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: NousResearch/Meta-Llama-3-8B |
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layer_range: [0, 1] |
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- sources: |
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- model: NousResearch/Meta-Llama-3-8B |
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layer_range: [1, 2] |
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- sources: |
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- model: NousResearch/Meta-Llama-3-8B |
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layer_range: [2, 3] |
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- sources: |
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- model: NousResearch/Meta-Llama-3-8B |
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layer_range: [3, 4] |
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- sources: |
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- model: NousResearch/Meta-Llama-3-8B |
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layer_range: [4, 5] |
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- sources: |
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- model: NousResearch/Meta-Llama-3-8B |
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layer_range: [5, 6] |
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- sources: |
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- model: NousResearch/Meta-Llama-3-8B |
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layer_range: [6, 7] |
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- sources: |
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- model: NousResearch/Meta-Llama-3-8B |
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layer_range: [7, 8] |
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- sources: |
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- model: NousResearch/Meta-Llama-3-8B |
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layer_range: [8, 9] |
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- sources: |
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- model: NousResearch/Meta-Llama-3-8B |
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layer_range: [9, 10] |
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- sources: |
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- model: NousResearch/Meta-Llama-3-8B |
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layer_range: [10, 11] |
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- sources: |
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- model: NousResearch/Meta-Llama-3-8B |
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layer_range: [11, 12] |
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- sources: |
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- model: NousResearch/Meta-Llama-3-8B |
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layer_range: [12, 13] |
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- sources: |
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- model: NousResearch/Meta-Llama-3-8B |
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layer_range: [13, 14] |
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- sources: |
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- model: NousResearch/Meta-Llama-3-8B |
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layer_range: [14, 15] |
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- sources: |
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- model: NousResearch/Meta-Llama-3-8B |
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layer_range: [30, 31] |
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merge_method: passthrough |
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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 = "ryan0712/llama-3-8b-slow-DUS-layer1-method2" |
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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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``` |
