初始化项目，由ModelHub XC社区提供模型

Model: jsfs11/WONMSeverusDevil-TIES-7B
Source: Original Platform

README.md

@@ -0,0 +1,87 @@
+---
+tags:
+- merge
+- mergekit
+- lazymergekit
+- FelixChao/WestSeverus-7B-DPO-v2
+- jsfs11/WestOrcaNeuralMarco-DPO-v2-DARETIES-7B
+- mlabonne/Daredevil-7B
+base_model:
+- FelixChao/WestSeverus-7B-DPO-v2
+- jsfs11/WestOrcaNeuralMarco-DPO-v2-DARETIES-7B
+- mlabonne/Daredevil-7B
+license: apache-2.0
+---
+
+# WONMSeverusDevil-TIES-7B
+
+WONMSeverusDevil-TIES-7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+* [FelixChao/WestSeverus-7B-DPO-v2](https://huggingface.co/FelixChao/WestSeverus-7B-DPO-v2)
+* [jsfs11/WestOrcaNeuralMarco-DPO-v2-DARETIES-7B](https://huggingface.co/jsfs11/WestOrcaNeuralMarco-DPO-v2-DARETIES-7B)
+* [mlabonne/Daredevil-7B](https://huggingface.co/mlabonne/Daredevil-7B)
+
+
+
+```
+# Open-LLM Benchmark Results:
+ WONMSeverusDevil-TIES-7B LLM AutoEval📑
+|       Model            |AGIEval|GPT4All|TruthfulQA|Bigbench|Average|
+|------------------------|------:|------:|---------:|-------:|------:|
+|WONMSeverusDevil-TIES-7B|  45.26|  77.07|     72.47|   48.85|  60.91|
+
+
+```
+
+
+# 🧩 Configuration
+
+```yaml
+models:
+  - model: FelixChao/WestSeverus-7B-DPO-v2
+    parameters:
+      density: [1, 0.7, 0.1] # density gradient
+      weight: 1.0
+  - model: jsfs11/WestOrcaNeuralMarco-DPO-v2-DARETIES-7B
+    parameters:
+      density: 0.65
+      weight: [0, 0.3, 0.7, 1] # weight gradient
+  - model: mlabonne/Daredevil-7B
+    parameters:
+      density: 0.33
+      weight:
+        - filter: mlp
+          value: 0.5
+        - value: 0
+merge_method: ties
+base_model: mistralai/Mistral-7B-v0.1
+parameters:
+  normalize: true
+  int8_mask: true
+dtype: float16
+
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "jsfs11/WONMSeverusDevil-TIES-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"])
+```