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Model: uproai/Rose-2x7B
Source: Original Platform

README.md

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+---
+license: apache-2.0
+tags:
+- moe
+- frankenmoe
+- merge
+- mergekit
+- maywell/PiVoT-0.1-Starling-LM-RP
+- WizardLM/WizardMath-7B-V1.1
+base_model:
+- maywell/PiVoT-0.1-Starling-LM-RP
+- WizardLM/WizardMath-7B-V1.1
+---
+
+# Rose-2x7B
+
+Rose-2x7B is a Mixure of Experts (MoE) made with the following models using [Mergekit](https://github.com/cg123/mergekit):
+* [maywell/PiVoT-0.1-Starling-LM-RP](https://huggingface.co/maywell/PiVoT-0.1-Starling-LM-RP)
+* [WizardLM/WizardMath-7B-V1.1](https://huggingface.co/WizardLM/WizardMath-7B-V1.1)
+
+```bash
+mergekit-moe mergekit_moe.yaml merge --copy-tokenizer --device cuda --low-cpu-memory
+```
+
+## 🧩 Configuration
+
+```yaml
+base_model: uproai/ros-7b-v1
+experts:
+  - source_model: maywell/PiVoT-0.1-Starling-LM-RP
+    positive_prompts:
+    - "storywriting"
+    - "write"
+    - "scene"
+    - "story"
+    - "character"
+  - source_model: WizardLM/WizardMath-7B-V1.1
+    positive_prompts:
+    - "reason"
+    - "math"
+    - "mathematics"
+    - "solve"
+    - "count"
+tokenizer_source: union
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers bitsandbytes accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "uproai/Rose-2x7B"
+
+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"])
+```