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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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- mistralai/Mistral-7B-Instruct-v0.2 |
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- beowolx/CodeNinja-1.0-OpenChat-7B |
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base_model: |
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- mistralai/Mistral-7B-Instruct-v0.2 |
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- beowolx/CodeNinja-1.0-OpenChat-7B |
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model-index: |
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- name: Hugo-7B-slerp |
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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: 64.51 |
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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=paulilioaica/Hugo-7B-slerp |
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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: 84.77 |
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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=paulilioaica/Hugo-7B-slerp |
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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: 62.54 |
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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=paulilioaica/Hugo-7B-slerp |
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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: 57.13 |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=paulilioaica/Hugo-7B-slerp |
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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: 80.03 |
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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=paulilioaica/Hugo-7B-slerp |
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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: 53.45 |
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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=paulilioaica/Hugo-7B-slerp |
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name: Open LLM Leaderboard |
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--- |
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# Hugo-7B-slerp |
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<p align="center"> |
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<img src="https://cdn.openart.ai/stable_diffusion/54be6f0516fee5ce9b3f8a8b68620a05059fc4cf_2000x2000.webp" alt="alt text" class="center" width="300"/> |
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</p> |
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Hugo-7B-slerp is a successful merge of the following models using mergekit: |
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* [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) |
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* [beowolx/CodeNinja-1.0-OpenChat-7B](https://huggingface.co/beowolx/CodeNinja-1.0-OpenChat-7B) |
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## ๐งฉ Configuration |
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```yaml |
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slices: |
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- sources: |
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- model: mistralai/Mistral-7B-Instruct-v0.2 |
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layer_range: [0, 32] |
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- model: beowolx/CodeNinja-1.0-OpenChat-7B |
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layer_range: [0, 32] |
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merge_method: slerp |
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base_model: mistralai/Mistral-7B-Instruct-v0.2 |
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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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## ๐ Performance |
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| Model | Average | ARC | HellaSwag | MMLU | TruthfulQA | Winogrande | GSM8K | |
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| --- | --- | --- | --- | --- | --- | --- | --- | |
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| [paulilioaica/Hugo-7B-slerp](#) | **67.07** | **64.51** | 84.77 | **62.54** | 57.13 | **80.03** | 53.45 | |
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| [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) | 65.71 | 63.14 | 84.88 | 60.78 | 68.26 | 77.19 | 40.03 | |
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| [beowolx/CodeNinja-1.0-OpenChat-7B](https://huggingface.co/beowolx/CodeNinja-1.0-OpenChat-7B) | 67.4 | 63.48 | 83.65 | 63.77 | 47.16 | 79.79 | 66.57 | |
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With bold one can see the benchmarks where this merge overtakes the basemodel in performance. |
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## ๐ป 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 = "paulilioaica/Hugo-7B-slerp" |
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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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pipeline = transformers.pipeline( |
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"conversational", |
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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(messages, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95) |
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print(outputs) |
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``` |
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## ๐ More on megekit |
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[mergekit](https://huggingface.co/blog/mlabonne/merge-models) |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_paulilioaica__Hugo-7B-slerp) |
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| Metric |Value| |
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|---------------------------------|----:| |
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|Avg. |67.07| |
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|AI2 Reasoning Challenge (25-Shot)|64.51| |
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|HellaSwag (10-Shot) |84.77| |
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|MMLU (5-Shot) |62.54| |
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|TruthfulQA (0-shot) |57.13| |
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|Winogrande (5-shot) |80.03| |
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|GSM8k (5-shot) |53.45| |
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