初始化项目，由ModelHub XC社区提供模型

Model: ichigoberry/MonarchPipe-7B-slerp
Source: Original Platform

README.md

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+---
+tags:
+- merge
+- mergekit
+- lazymergekit
+- OpenPipe/mistral-ft-optimized-1227
+- mlabonne/AlphaMonarch-7B
+base_model:
+- OpenPipe/mistral-ft-optimized-1227
+- mlabonne/AlphaMonarch-7B
+license: cc-by-nc-2.0
+---
+
+<img src="https://cdn-uploads.huggingface.co/production/uploads/6389d3c61e8755d777902366/7dTpG4vJWkB4YwBJFCqoE.jpeg" style="border-radius:2%; width: 66%">
+
+# MonarchPipe-7B-slerp
+
+MonarchPipe-7B-slerp is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+* [OpenPipe/mistral-ft-optimized-1227](https://huggingface.co/OpenPipe/mistral-ft-optimized-1227)
+* [mlabonne/AlphaMonarch-7B](https://huggingface.co/mlabonne/AlphaMonarch-7B)
+
+
+## 🏆 Eval
+
+### Nous
+
+Eval results from the Nous benchmark suite (performed using LLM AutoEval).
+
+| Model | Average | AGIEval | GPT4All | TruthfulQA | Bigbench |
+|---|---:|---:|---:|---:|---:|
+| [**MonarchPipe-7B-slerp**](https://huggingface.co/ichigoberry/MonarchPipe-7B-slerp) [📄](https://gist.github.com/tosh/3d93f4e3d2c65935bf2f4f9a46791352)| 58.77|  **46.12**|  74.89|     66.59|   47.49|
+| [AlphaMonarch-7B](https://huggingface.co/mlabonne/AlphaMonarch-7B) [📄](https://gist.github.com/mlabonne/1d33c86824b3a11d2308e36db1ba41c1) | **62.74** | 45.37 | **77.01** | **78.39** | **50.2** |
+| [Monarch-7B](https://huggingface.co/mlabonne/Monarch-7B) [📄](https://gist.github.com/mlabonne/0b8d057c5ece41e0290580a108c7a093) | 62.68 | 45.48 | 77.07 | 78.04 | 50.14 |
+| [OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) [📄](https://gist.github.com/mlabonne/88b21dd9698ffed75d6163ebdc2f6cc8) | 52.42 | 42.75 | 72.99 | 52.99 | 40.94 |
+| [NeuralHermes-2.5-Mistral-7B](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B) [📄](https://gist.github.com/mlabonne/14687f1eb3425b166db511f31f8e66f6) | 53.51 | 43.67 | 73.24 | 55.37 | 41.76 |
+
+
+
+## 🧩 Configuration
+
+```yaml
+slices:
+  - sources:
+      - model: OpenPipe/mistral-ft-optimized-1227
+        layer_range: [0, 32]
+      - model: mlabonne/AlphaMonarch-7B
+        layer_range: [0, 32]
+merge_method: slerp
+base_model: OpenPipe/mistral-ft-optimized-1227
+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 = "ichigoberry/MonarchPipe-7B-slerp"
+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"])
+```