初始化项目，由ModelHub XC社区提供模型

Model: CultriX/SevereNeuralBeagleTrix-7B
Source: Original Platform

README.md

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+---
+tags:
+- merge
+- mergekit
+- lazymergekit
+- PetroGPT/WestSeverus-7B-DPO
+- CultriX/MergeTrix-7B-v2
+- mlabonne/NeuralBeagle14-7B
+base_model:
+- PetroGPT/WestSeverus-7B-DPO
+- CultriX/MergeTrix-7B-v2
+- mlabonne/NeuralBeagle14-7B
+license: apache-2.0
+---
+
+# EDIT:
+Always check my space for the latest benchmark results for my models!
+* https://huggingface.co/spaces/CultriX/Yet_Another_LLM_Leaderboard
+
+# SevereNeuralBeagleTrix-7B
+
+SevereNeuralBeagleTrix-7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+* [PetroGPT/WestSeverus-7B-DPO](https://huggingface.co/PetroGPT/WestSeverus-7B-DPO)
+* [CultriX/MergeTrix-7B-v2](https://huggingface.co/CultriX/MergeTrix-7B-v2)
+* [mlabonne/NeuralBeagle14-7B](https://huggingface.co/mlabonne/NeuralBeagle14-7B)
+
+## 🧩 Configuration
+
+```yaml
+models:
+  - model: mistralai/Mistral-7B-v0.1
+    # No parameters necessary for base model
+  - model: PetroGPT/WestSeverus-7B-DPO
+    parameters:
+      density: 0.53
+      weight: 0.3
+  - model: CultriX/MergeTrix-7B-v2
+    parameters:
+      density: 0.53
+      weight: 0.4
+  - model: mlabonne/NeuralBeagle14-7B
+    parameters:
+      density: 0.53
+      weight: 0.3
+merge_method: dare_ties
+base_model: mistralai/Mistral-7B-v0.1
+parameters:
+  int8_mask: true
+dtype: float16
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "CultriX/SevereNeuralBeagleTrix-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"])
+```