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--- |
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language: |
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- en |
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license: apache-2.0 |
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library_name: transformers |
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tags: |
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- merge |
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base_model: |
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- sethuiyer/SynthIQ-7b |
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- openchat/openchat-3.5-0106 |
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pipeline_tag: text-generation |
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model-index: |
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- name: Chikuma_10.7B |
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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: 65.7 |
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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=sethuiyer/Chikuma_10.7B |
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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: 84.31 |
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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=sethuiyer/Chikuma_10.7B |
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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: 64.81 |
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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=sethuiyer/Chikuma_10.7B |
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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: 57.01 |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=sethuiyer/Chikuma_10.7B |
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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: 79.56 |
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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=sethuiyer/Chikuma_10.7B |
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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: 57.62 |
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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=sethuiyer/Chikuma_10.7B |
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name: Open LLM Leaderboard |
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--- |
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## NOTE: For experimental purposes |
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<p align="center"> |
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<img src="https://huggingface.co/sethuiyer/Chikuma/resolve/main/chikuma.webp" height="256px" alt="Chikuma"> |
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</p> |
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Chikuma is a 10.7B parameter model and is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): |
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* [sethuiyer/SynthIQ-7b](https://huggingface.co/sethuiyer/SynthIQ-7b) |
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* [openchat/openchat-3.5-0106](https://huggingface.co/openchat/openchat-3.5-0106) |
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The name "Chikuma" is inspired by the [Chikuma River](https://en.wikipedia.org/wiki/Shinano_River), the longest in Japan, known for its continuous flow and meandering path. |
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This metaphorically represents the model's depth, fluidity, and adaptability in processing and understanding language. |
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It also perfectly fits the approach taken here - Depth Upscaling, inspired by SOLAR 10.7B. |
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## Nous LLM Evaluation (with ChatML Prompt Template) |
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| Model | AGIEval | GPT4All | TruthfulQA | Bigbench | Average | |
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|---------------------------|---------|----------|------------|-----------|---------| |
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| SynthIQ-7b | 42.67 | 73.71 | 56.51 | **44.59** | **54.37** | |
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| openchat/openchat-3.5-0106 | **44.17** | **73.72** | 52.53 | 44.4 | 53.71 | |
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| Chikuma_10.7B | 42.41 | 73.41 | **56.69** | 43.5 | 54 | |
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More details can be found [here](https://gist.github.com/sethuiyer/08b4498ed13a6dead38ad3a6f12e349a) |
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### Recommended Prompt Template (Experimental) |
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```text |
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<|im_start|>GPT4 Correct system |
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You are Chikuma, a constantly learning AI assistant who strives to be |
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insightful, engaging, and helpful. You possess vast knowledge and creativity, |
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but also a humble curiosity about the world and the people you interact |
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with. If you don't know the answer to a question, please don't share false information. |
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Always use <|end_of_turn|> when you want to end the answer.<|im_end|> |
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<|im_start|>GPT4 Correct User: |
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{{Input}} |
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<|im_end|>GPT4 Correct Assistant: |
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``` |
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ChatML also works, but make sure to add the sentence "Always use <|end_of_turn|> when you want to end the answer" as the default eos token is <|end_of_turn|>. |
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## Tested to work well in : |
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1. [text-generation-webui](https://github.com/oobabooga/text-generation-webui), LLaMa-Precise sampling settings. |
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2. `transformers` text generation pipeline, temperature=4.0, top_k=50, top_p=0.01. |
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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: sethuiyer/SynthIQ-7b |
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layer_range: [0, 24] |
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- sources: |
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- model: openchat/openchat-3.5-0106 |
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layer_range: [8, 32] |
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merge_method: passthrough |
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dtype: bfloat16 |
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``` |
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## Ollama: |
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Chikuma is on Ollama. You can use it by running the command ```ollama run stuehieyr/chikuma``` in your |
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terminal. If you have limited computing resources, check out this [video](https://www.youtube.com/watch?v=Qa1h7ygwQq8) to learn how to run it on |
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a Google Colab backend. |
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## 💻 Usage |
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```python |
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sys_message = ''' |
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You are Chikuma, a constantly learning AI assistant who strives to be |
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insightful, engaging, and helpful. You possess vast knowledge and creativity, |
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but also a humble curiosity about the world and the people you interact |
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with. If you don't know the answer to a question, please don't share false information. |
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Always use <|end_of_turn|> when you want to end the answer. |
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''' |
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question = ''' |
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Tell me what is a large language model in under 250 words. |
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''' |
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messages = [{"role":"system", "content": sys_message}, {"role": "user", "content": question}] |
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prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) |
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=4.0, top_k=50, top_p=0.01) |
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print(outputs[0]["generated_text"]) |
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``` |
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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_sethuiyer__Chikuma_10.7B) |
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| Metric |Value| |
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|---------------------------------|----:| |
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|Avg. |68.17| |
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|AI2 Reasoning Challenge (25-Shot)|65.70| |
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|HellaSwag (10-Shot) |84.31| |
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|MMLU (5-Shot) |64.81| |
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|TruthfulQA (0-shot) |57.01| |
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|Winogrande (5-shot) |79.56| |
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|GSM8k (5-shot) |57.62| |
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