初始化项目，由ModelHub XC社区提供模型
Model: sethuiyer/Chikuma_10.7B Source: Original Platform
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README.md
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README.md
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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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