初始化项目，由ModelHub XC社区提供模型

Model: Kukedlc/Ramakrishna-7b-v3
Source: Original Platform

README.md

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+---
+tags:
+- merge
+- mergekit
+- lazymergekit
+- automerger/YamShadow-7B
+- Kukedlc/Neural4gsm8k
+- Kukedlc/NeuralSirKrishna-7b
+- mlabonne/NeuBeagle-7B
+- Kukedlc/Ramakrishna-7b
+- Kukedlc/NeuralGanesha-7b
+base_model:
+- automerger/YamShadow-7B
+- Kukedlc/Neural4gsm8k
+- Kukedlc/NeuralSirKrishna-7b
+- mlabonne/NeuBeagle-7B
+- Kukedlc/Ramakrishna-7b
+- Kukedlc/NeuralGanesha-7b
+license: apache-2.0
+---
+
+# Ramakrishna-7b-v3
+
+Ramakrishna-7b-v3 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+* [automerger/YamShadow-7B](https://huggingface.co/automerger/YamShadow-7B)
+* [Kukedlc/Neural4gsm8k](https://huggingface.co/Kukedlc/Neural4gsm8k)
+* [Kukedlc/NeuralSirKrishna-7b](https://huggingface.co/Kukedlc/NeuralSirKrishna-7b)
+* [mlabonne/NeuBeagle-7B](https://huggingface.co/mlabonne/NeuBeagle-7B)
+* [Kukedlc/Ramakrishna-7b](https://huggingface.co/Kukedlc/Ramakrishna-7b)
+* [Kukedlc/NeuralGanesha-7b](https://huggingface.co/Kukedlc/NeuralGanesha-7b)
+
+## 🧩 Configuration
+
+```yaml
+models:
+  - model: automerger/YamShadow-7B
+    # No parameters necessary for base model
+  - model: automerger/YamShadow-7B
+    parameters:
+      density: 0.6
+      weight: 0.2
+  - model: Kukedlc/Neural4gsm8k
+    parameters:
+      density: 0.3
+      weight: 0.1
+  - model: Kukedlc/NeuralSirKrishna-7b
+    parameters:
+      density: 0.6
+      weight: 0.2
+  - model: mlabonne/NeuBeagle-7B
+    parameters:
+      density: 0.5
+      weight: 0.15
+  - model: Kukedlc/Ramakrishna-7b
+    parameters:
+      density: 0.6
+      weight: 0.25
+  - model: Kukedlc/NeuralGanesha-7b
+    parameters:
+      density: 0.6
+      weight: 0.1
+merge_method: dare_ties
+base_model: automerger/YamShadow-7B
+parameters:
+  int8_mask: true
+dtype: bfloat16
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "Kukedlc/Ramakrishna-7b-v3"
+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"])
+```