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--- |
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license: apache-2.0 |
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tags: |
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- moe |
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- frankenmoe |
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- merge |
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- mergekit |
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- lazymergekit |
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- mlabonne/AlphaMonarch-7B |
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- bardsai/jaskier-7b-dpo-v5.6 |
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base_model: |
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- mlabonne/AlphaMonarch-7B |
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- bardsai/jaskier-7b-dpo-v5.6 |
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--- |
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# ExpertRamonda-7Bx2_MoE |
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ExpertRamonda-7Bx2_MoE is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): |
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* [mlabonne/AlphaMonarch-7B](https://huggingface.co/mlabonne/AlphaMonarch-7B) |
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* [bardsai/jaskier-7b-dpo-v5.6](https://huggingface.co/bardsai/jaskier-7b-dpo-v5.6) |
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# 🏆 Benchmarks |
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### Open LLM Leaderboard |
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| Model | Average | ARC_easy | HellaSwag | MMLU | TruthfulQA_mc2 | Winogrande | GSM8K | |
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|------------------------|--------:|-----:|----------:|-----:|-----------:|-----------:|------:| |
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| mayacinka/ExpertRamonda-7Bx2_MoE | 78.10 | 86.87 | 87.51| 61.63 | 78.02 | 81.85 | 72.71| |
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### MMLU |
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| Groups |Version|Filter|n-shot|Metric|Value | |Stderr| |
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|------------------|-------|------|------|------|-----:|---|-----:| |
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|mmlu |N/A |none | 0|acc |0.6163|± |0.0039| |
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| - humanities |N/A |none |None |acc |0.5719|± |0.0067| |
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| - other |N/A |none |None |acc |0.6936|± |0.0079| |
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| - social_sciences|N/A |none |None |acc |0.7121|± |0.0080| |
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| - stem |N/A |none |None |acc |0.5128|± |0.0085| |
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## 🧩 Configuration |
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```yaml |
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base_model: mlabonne/AlphaMonarch-7B |
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gate_mode: hidden |
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dtype: bfloat16 |
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experts_per_token: 2 |
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experts: |
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- source_model: mlabonne/AlphaMonarch-7B |
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positive_prompts: |
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- "You excel at reasoning skills. For every prompt you think of an answer from 3 different angles" |
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## (optional) |
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# negative_prompts: |
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# - "This is a prompt expert_model_1 should not be used for" |
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- source_model: bardsai/jaskier-7b-dpo-v5.6 |
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positive_prompts: |
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- "You excel at logic and reasoning skills. Reply in a straightforward and concise way" |
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``` |
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## 💻 Usage |
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```python |
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!pip install -qU transformers bitsandbytes 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 = "mayacinka/ExpertRamonda-7Bx2_MoE" |
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tokenizer = AutoTokenizer.from_pretrained(model) |
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pipeline = transformers.pipeline( |
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"text-generation", |
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model=model, |
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model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True}, |
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) |
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messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}] |
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prompt = pipeline.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=0.7, top_k=50, top_p=0.95) |
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print(outputs[0]["generated_text"]) |
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``` |