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Model: Ppoyaa/StarMonarch-7B Source: Original Platform
2026-05-10 09:23:22 +08:00
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+---
+tags:
+- merge
+- mergekit
+- lazymergekit
+base_model:
+- mlabonne/AlphaMonarch-7B
+- Nexusflow/Starling-LM-7B-beta
+license: apache-2.0
+language:
+- en
+---
+
+# StarMonarch-7B
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/65f158693196560d34495d54/kY82CwYmaGSt2k3iWjOOZ.png)
+# Description
+
+StarMonarch-7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+* [mlabonne/AlphaMonarch-7B](https://huggingface.co/mlabonne/AlphaMonarch-7B)
+* [Nexusflow/Starling-LM-7B-beta](https://huggingface.co/Nexusflow/Starling-LM-7B-beta)
+
+This model uses a context window of 8k. Special thanks to mlabonne and Nexusflow for the models.
+
+## 🏆 Open LLM Leaderboard Evaluation Results 
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |74.45|
+|AI2 Reasoning Challenge (25-Shot)|71.25|
+|HellaSwag (10-Shot)              |87.00|
+|MMLU (5-Shot)                    |65.48|
+|TruthfulQA (0-shot)              |67.20|
+|Winogrande (5-shot)              |82.16|
+|GSM8k (5-shot)                   |73.62|
+
+## 🧩 Configuration
+
+```yaml
+slices:
+  - sources:
+      - model: mlabonne/AlphaMonarch-7B
+        layer_range: [0, 32]
+      - model: Nexusflow/Starling-LM-7B-beta
+        layer_range: [0, 32]
+merge_method: slerp
+base_model: mlabonne/AlphaMonarch-7B
+parameters:
+  t:
+    - filter: self_attn
+      value: [0, 0.5, 0.3, 0.7, 1]
+    - filter: mlp
+      value: [1, 0.5, 0.7, 0.3, 0]
+    - value: 0.5
+dtype: bfloat16
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "Ppoyaa/StarMonarch-7B"
+messages = [{"role": "user", "content": "What is a large language model?"}]
+
+tokenizer = AutoTokenizer.from_pretrained(model)
+prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model,
+    torch_dtype=torch.float16,
+    device_map="auto",
+)
+
+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"])
+```