77 lines
2.7 KiB
Markdown
77 lines
2.7 KiB
Markdown
---
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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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- NousResearch/Meta-Llama-3-8B-Instruct
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- NousResearch/Meta-Llama-3-8B-Instruct
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- NousResearch/Meta-Llama-3-8B-Instruct
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- NousResearch/Meta-Llama-3-8B-Instruct
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- NousResearch/Meta-Llama-3-8B-Instruct
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---
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# Meta-Llama-3-12B-Instruct
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Meta-Llama-3-12B-Instruct 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-Instruct](https://huggingface.co/NousResearch/Meta-Llama-3-8B-Instruct)
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* [NousResearch/Meta-Llama-3-8B-Instruct](https://huggingface.co/NousResearch/Meta-Llama-3-8B-Instruct)
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* [NousResearch/Meta-Llama-3-8B-Instruct](https://huggingface.co/NousResearch/Meta-Llama-3-8B-Instruct)
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* [NousResearch/Meta-Llama-3-8B-Instruct](https://huggingface.co/NousResearch/Meta-Llama-3-8B-Instruct)
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* [NousResearch/Meta-Llama-3-8B-Instruct](https://huggingface.co/NousResearch/Meta-Llama-3-8B-Instruct)
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## 🏆 Evaluation
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| Model |AGIEval|GPT4All|TruthfulQA|Bigbench|Average|
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|--------------------------------------------------------------------------------------|------:|------:|---------:|-------:|------:|
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|[Meta-Llama-3-12B-Instruct](https://huggingface.co/mlabonne/Meta-Llama-3-12B-Instruct)| 41.7| 67.71| 52.75| 40.58| 50.69|
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|[Meta-Llama-3-12B](https://huggingface.co/mlabonne/Meta-Llama-3-12B)| 29.46| 68.01| 41.02| 35.57| 43.52|
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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-Instruct
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layer_range: [0,9]
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- sources:
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- model: NousResearch/Meta-Llama-3-8B-Instruct
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layer_range: [5,14]
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- sources:
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- model: NousResearch/Meta-Llama-3-8B-Instruct
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layer_range: [10,19]
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- sources:
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- model: NousResearch/Meta-Llama-3-8B-Instruct
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layer_range: [15,24]
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- sources:
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- model: NousResearch/Meta-Llama-3-8B-Instruct
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layer_range: [20,32]
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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 = "mlabonne/Meta-Llama-3-12B-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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``` |