182 lines
5.2 KiB
Markdown
182 lines
5.2 KiB
Markdown
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---
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license: cc-by-nc-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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- SanjiWatsuki/Kunoichi-DPO-v2-7B
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- mlabonne/AlphaMonarch-7B
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base_model:
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- SanjiWatsuki/Kunoichi-DPO-v2-7B
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- mlabonne/AlphaMonarch-7B
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model-index:
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- name: kuno-dogwalker-7b
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: AI2 Reasoning Challenge (25-Shot)
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type: ai2_arc
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config: ARC-Challenge
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split: test
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args:
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num_few_shot: 25
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metrics:
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- type: acc_norm
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value: 72.01
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=core-3/kuno-dogwalker-7b
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: HellaSwag (10-Shot)
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type: hellaswag
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split: validation
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args:
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num_few_shot: 10
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metrics:
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- type: acc_norm
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value: 88.17
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=core-3/kuno-dogwalker-7b
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU (5-Shot)
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type: cais/mmlu
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config: all
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 64.96
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=core-3/kuno-dogwalker-7b
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: TruthfulQA (0-shot)
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type: truthful_qa
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config: multiple_choice
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split: validation
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args:
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num_few_shot: 0
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metrics:
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- type: mc2
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value: 71.39
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=core-3/kuno-dogwalker-7b
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: Winogrande (5-shot)
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type: winogrande
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config: winogrande_xl
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split: validation
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 82.0
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=core-3/kuno-dogwalker-7b
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: GSM8k (5-shot)
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type: gsm8k
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 71.11
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=core-3/kuno-dogwalker-7b
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name: Open LLM Leaderboard
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---
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# kuno-dogwalker-7b
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# 🦮🦮🦮🥷
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Decent metrics, but writing feels off compared to [kuno-royale-v2-7b](https://huggingface.co/core-3/kuno-royale-v2-7b).
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|Model | Average | ARC | HellaSwag | MMLU | TruthfulQA | Winogrande | GSM8K |
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|-------------------|---------|-----|-----------|------|------------|------------|-------|
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| eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO | 76.45 | 73.12 | 89.09 | 64.80 | 77.45 | 84.77 | 69.45 |
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| mlabonne/AlphaMonarch-7B | 75.99 | 73.04 | 89.18 | 64.40 | 77.91 | 84.69 | 66.72 |
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| **core-3/kuno-dogwalker-7b** | **74.94** | **72.01** | **88.17** | **64.96** | **71.39** | **82.00** | **71.11** |
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| core-3/kuno-royale-v2-7b | 74.80 | 72.01 | 88.15 | 65.07 | 71.10 | 82.24 | 70.20 |
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| core-3/kuno-royale-7B | 74.74 | 71.76 | 88.20 | 65.13 | 71.12 | 82.32 | 69.90 |
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| SanjiWatsuki/Kunoichi-DPO-v2-7B | 72.46 | 69.62 | 87.44 | 64.94 | 66.06 | 80.82 | 65.88 |
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| SanjiWatsuki/Kunoichi-7B | 72.13 | 68.69 | 87.10 | 64.90 | 64.04 | 81.06 | 67.02 |
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kuno-dogwalker-7b is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [SanjiWatsuki/Kunoichi-DPO-v2-7B](https://huggingface.co/SanjiWatsuki/Kunoichi-DPO-v2-7B)
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* [mlabonne/AlphaMonarch-7B](https://huggingface.co/mlabonne/AlphaMonarch-7B)
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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: SanjiWatsuki/Kunoichi-DPO-v2-7B
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layer_range: [0, 32]
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- model: mlabonne/AlphaMonarch-7B
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layer_range: [0, 32]
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merge_method: slerp
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base_model: SanjiWatsuki/Kunoichi-DPO-v2-7B
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parameters:
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t:
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- filter: self_attn
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value: [0, 0.5, 0.3, 0.7, 1]
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- filter: mlp
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value: [1, 0.5, 0.7, 0.3, 0]
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- value: 0.5
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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 = "core-3/kuno-dogwalker-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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```
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