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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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- mergekit |
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--- |
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# Beyonder-4x7b |
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This model is a Mixure of Experts (MoE) made with [mergekit](https://github.com/cg123/mergekit) (mixtral branch). It uses the following base models: |
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* [openchat/openchat-3.5-1210](https://huggingface.co/openchat/openchat-3.5-1210) |
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* [beowolx/CodeNinja-1.0-OpenChat-7B](https://huggingface.co/beowolx/CodeNinja-1.0-OpenChat-7B) |
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* [maywell/PiVoT-0.1-Starling-LM-RP](https://huggingface.co/maywell/PiVoT-0.1-Starling-LM-RP) |
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* [WizardLM/WizardMath-7B-V1.1](https://huggingface.co/WizardLM/WizardMath-7B-V1.1) |
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## 🧩 Configuration |
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```yaml |
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base_model: openchat/openchat-3.5-1210 |
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gate_mode: hidden |
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experts: |
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- source_model: openchat/openchat-3.5-1210 |
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positive_prompts: |
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- "chat" |
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- "assistant" |
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- "tell me" |
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- "explain" |
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negative_prompts: |
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- "storywriting" |
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- "mathematics" |
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- "reasoning" |
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- "code" |
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- "programming" |
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- source_model: beowolx/CodeNinja-1.0-OpenChat-7B |
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positive_prompts: |
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- "code" |
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- "python" |
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- "javascript" |
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- "programming" |
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- "algorithm" |
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negative_prompts: |
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- "chat" |
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- "assistant" |
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- "storywriting" |
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- "mathematics" |
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- "reasoning" |
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- source_model: maywell/PiVoT-0.1-Starling-LM-RP |
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positive_prompts: |
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- "storywriting" |
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- "write" |
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- "scene" |
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- "story" |
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- "character" |
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negative_prompts: |
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- "chat" |
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- "assistant" |
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- "code" |
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- "programming" |
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- "mathematics" |
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- "reasoning" |
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- source_model: WizardLM/WizardMath-7B-V1.1 |
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positive_prompts: |
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- "reason" |
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- "math" |
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- "mathematics" |
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- "solve" |
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- "count" |
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negative_prompts: |
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- "chat" |
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- "assistant" |
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- "code" |
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- "programming" |
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- "storywriting" |
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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 = "mlabonne/Beyonder-4x7b" |
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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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``` |
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Output: |
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``` |
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A Mixture of Experts (MoE) is a neural network architecture that combines the strengths of multiple expert networks to make predictions. It leverages the idea of ensemble learning, where multiple models work together to improve performance. In each MoE, a gating network is used to select the most relevant expert for the input. The final output is a weighted combination of the expert outputs, determined by the gating network's predictions. |
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``` |
