Create README.md

README.md

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+---
+tags:
+- merge
+- mergekit
+- lazymergekit
+- Kukedlc/NeuTrixOmniBe-7B-model-remix
+- PetroGPT/WestSeverus-7B-DPO
+- vanillaOVO/supermario_v4
+base_model:
+- Kukedlc/NeuTrixOmniBe-7B-model-remix
+- PetroGPT/WestSeverus-7B-DPO
+- vanillaOVO/supermario_v4
+---
+
+# MoEv4Config-TestWeightedTIES-7b
+
+MoEv4Config-TestWeightedTIES-7b is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+* [Kukedlc/NeuTrixOmniBe-7B-model-remix](https://huggingface.co/Kukedlc/NeuTrixOmniBe-7B-model-remix)
+* [PetroGPT/WestSeverus-7B-DPO](https://huggingface.co/PetroGPT/WestSeverus-7B-DPO)
+* [vanillaOVO/supermario_v4](https://huggingface.co/vanillaOVO/supermario_v4)
+
+## 🧩 Configuration
+
+```yaml
+models:
+  - model: Kukedlc/NeuTrixOmniBe-7B-model-remix
+    # No parameters necessary for base model
+  - model: Kukedlc/NeuTrixOmniBe-7B-model-remix
+    parameters:
+      density: [1, 0.7, 0.1]
+      weight: [0, 0.3, 0.7, 1]
+  - model: PetroGPT/WestSeverus-7B-DPO
+    parameters:
+      density: [1, 0.7, 0.3]
+      weight: [0, 0.25, 0.5, 1]
+  - model: vanillaOVO/supermario_v4
+    parameters:
+      density: 0.33
+      weight:
+        - filter: mlp
+          value: 0.5
+        - value: 0
+merge_method: ties
+base_model: Kukedlc/NeuTrixOmniBe-7B-model-remix
+parameters:
+  int8_mask: true
+  normalize: true
+  sparsify:
+    - filter: mlp
+      value: 0.5
+    - filter: self_attn
+      value: 0.5
+dtype: bfloat16
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "jsfs11/MoEv4Config-TestWeightedTIES-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"])
+```