72 lines
1.9 KiB
Markdown
72 lines
1.9 KiB
Markdown
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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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- Kukedlc/NeuralGlitch-Yam-Peleg-7B-DT
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- Kukedlc/Fasciculus-Arcuatus-7B-slerp
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- Kukedlc/Neural4gsm8k
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base_model:
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- Kukedlc/NeuralGlitch-Yam-Peleg-7B-DT
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- Kukedlc/Fasciculus-Arcuatus-7B-slerp
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- Kukedlc/Neural4gsm8k
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license: apache-2.0
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---
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# NeuralKrishna-7B-v3
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NeuralKrishna-7B-v3 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [Kukedlc/NeuralGlitch-Yam-Peleg-7B-DT](https://huggingface.co/Kukedlc/NeuralGlitch-Yam-Peleg-7B-DT)
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* [Kukedlc/Fasciculus-Arcuatus-7B-slerp](https://huggingface.co/Kukedlc/Fasciculus-Arcuatus-7B-slerp)
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* [Kukedlc/Neural4gsm8k](https://huggingface.co/Kukedlc/Neural4gsm8k)
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## 🧩 Configuration
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```yaml
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models:
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- model: mlabonne/Monarch-7B
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# no parameters necessary for base model
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- model: Kukedlc/NeuralGlitch-Yam-Peleg-7B-DT
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parameters:
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density: 0.65
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weight: 0.36
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- model: Kukedlc/Fasciculus-Arcuatus-7B-slerp
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parameters:
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density: 0.6
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weight: 0.34
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- model: Kukedlc/Neural4gsm8k
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parameters:
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density: 0.6
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weight: 0.3
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merge_method: dare_ties
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base_model: mlabonne/Monarch-7B
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parameters:
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int8_mask: true
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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 = "Kukedlc/NeuralKrishna-7B-v3"
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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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