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--- |
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license: apache-2.0 |
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tags: |
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- merge |
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- mergekit |
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- lazymergekit |
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- automerger |
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base_model: |
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- liminerity/M7-7b |
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- AurelPx/Percival_01-7b-slerp |
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--- |
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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: liminerity/M7-7b |
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layer_range: [0, 32] |
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- model: AurelPx/Percival_01-7b-slerp |
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layer_range: [0, 32] |
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merge_method: slerp |
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base_model: liminerity/M7-7b |
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parameters: |
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t: |
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- filter: self_attn |
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value: [0.8006027834577485, 0.009328524130124638, 0.8621983214027452, 0.3145686958412437, 0.15715134219207227] |
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- filter: mlp |
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value: [0.1993972165422515, 0.9906714758698754, 0.13780167859725478, 0.6854313041587563, 0.8428486578079277] |
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- value: 0.9507953064688142 |
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dtype: bfloat16 |
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random_seed: 0 |
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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 = "aaron-di/Yamshadowexperiment28M70.8-0.01-0.86-0.31-0.16-0.95-7B" |
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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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``` |
