Adding Evaluation Results (#1)

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	---
	license: apache-2.0
	tags:
	- moe
	- frankenmoe
	- merge
	- mergekit
	- lazymergekit
	- indischepartij/MiniCPM-3B-Hercules-v2.0
	- indischepartij/MiniCPM-3B-OpenHermes-2.5-v2
	- indischepartij/MiniCPM-3B-Bacchus
	base_model:
	- indischepartij/MiniCPM-3B-Hercules-v2.0
	- indischepartij/MiniCPM-3B-OpenHermes-2.5-v2
	- indischepartij/MiniCPM-3B-Bacchus
	model-index:
	- name: MaxiCPM-3x3B-Test
	results:
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: AI2 Reasoning Challenge (25-Shot)
	type: ai2_arc
	config: ARC-Challenge
	split: test
	args:
	num_few_shot: 25
	metrics:
	- type: acc_norm
	value: 45.99
	name: normalized accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=gmonsoon/MaxiCPM-3x3B-Test
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: HellaSwag (10-Shot)
	type: hellaswag
	split: validation
	args:
	num_few_shot: 10
	metrics:
	- type: acc_norm
	value: 71.74
	name: normalized accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=gmonsoon/MaxiCPM-3x3B-Test
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: MMLU (5-Shot)
	type: cais/mmlu
	config: all
	split: test
	args:
	num_few_shot: 5
	metrics:
	- type: acc
	value: 52.88
	name: accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=gmonsoon/MaxiCPM-3x3B-Test
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: TruthfulQA (0-shot)
	type: truthful_qa
	config: multiple_choice
	split: validation
	args:
	num_few_shot: 0
	metrics:
	- type: mc2
	value: 41.06
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=gmonsoon/MaxiCPM-3x3B-Test
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: Winogrande (5-shot)
	type: winogrande
	config: winogrande_xl
	split: validation
	args:
	num_few_shot: 5
	metrics:
	- type: acc
	value: 66.85
	name: accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=gmonsoon/MaxiCPM-3x3B-Test
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: GSM8k (5-shot)
	type: gsm8k
	config: main
	split: test
	args:
	num_few_shot: 5
	metrics:
	- type: acc
	value: 44.88
	name: accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=gmonsoon/MaxiCPM-3x3B-Test
	name: Open LLM Leaderboard
	---

	# MaxiCPM-3x3B-Test

	MaxiCPM-3x3B-Test is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
	* [indischepartij/MiniCPM-3B-Hercules-v2.0](https://huggingface.co/indischepartij/MiniCPM-3B-Hercules-v2.0)
	* [indischepartij/MiniCPM-3B-OpenHermes-2.5-v2](https://huggingface.co/indischepartij/MiniCPM-3B-OpenHermes-2.5-v2)
	* [indischepartij/MiniCPM-3B-Bacchus](https://huggingface.co/indischepartij/MiniCPM-3B-Bacchus)

	## 🧩 Configuration

	```yaml
	base_model: openbmb/MiniCPM-2B-dpo-bf16-llama-format
	experts:
	- source_model: indischepartij/MiniCPM-3B-Hercules-v2.0
	positive_prompts:
	- "chat"
	- "assistant"
	- "tell me"
	- "explain"
	- source_model: indischepartij/MiniCPM-3B-OpenHermes-2.5-v2
	positive_prompts:
	- "code"
	- "python"
	- "javascript"
	- "programming"
	- "algorithm"
	- source_model: indischepartij/MiniCPM-3B-Bacchus
	positive_prompts:
	- "storywriting"
	- "write"
	- "scene"
	- "story"
	- "character"
	- "reason"
	- "math"
	- "mathematics"
	- "solve"
	- "count"
	dtype: bfloat16
	```

	## 💻 Usage

	```python
	!pip install -qU transformers bitsandbytes accelerate

	from transformers import AutoTokenizer
	import transformers
	import torch

	model = "gmonsoon/MaxiCPM-3x3B-Test"

	tokenizer = AutoTokenizer.from_pretrained(model)
	pipeline = transformers.pipeline(
	"text-generation",
	model=model,
	model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
	)

	messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
	prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
	outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
	print(outputs[0]["generated_text"])
	```
	# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
	Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_gmonsoon__MaxiCPM-3x3B-Test)

	\| Metric \|Value\|
	\|---------------------------------\|----:\|
	\|Avg. \|53.90\|
	\|AI2 Reasoning Challenge (25-Shot)\|45.99\|
	\|HellaSwag (10-Shot) \|71.74\|
	\|MMLU (5-Shot) \|52.88\|
	\|TruthfulQA (0-shot) \|41.06\|
	\|Winogrande (5-shot) \|66.85\|
	\|GSM8k (5-shot) \|44.88\|