Create README.md

README.md

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+---
+tags:
+- merge
+- mergekit
+- lazymergekit
+- mlabonne/OmniTruthyBeagle-7B-v0
+- mayflowergmbh/Wiedervereinigung-7b-dpo-laser
+- cognitivecomputations/openchat-3.5-0106-laser
+base_model:
+- mlabonne/OmniTruthyBeagle-7B-v0
+- mayflowergmbh/Wiedervereinigung-7b-dpo-laser
+- cognitivecomputations/openchat-3.5-0106-laser
+---
+
+# Wiederchat-7b-dpo-laser
+
+Wiederchat-7b-dpo is a laser-qlorad dpo-aligned merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+* [mlabonne/OmniTruthyBeagle-7B-v0](https://huggingface.co/mlabonne/OmniTruthyBeagle-7B-v0)
+* [mayflowergmbh/Wiedervereinigung-7b-dpo-laser](https://huggingface.co/mayflowergmbh/Wiedervereinigung-7b-dpo-laser)
+* [cognitivecomputations/openchat-3.5-0106-laser](https://huggingface.co/cognitivecomputations/openchat-3.5-0106-laser)
+
+## 🧩 Configuration
+
+```yaml
+models:
+  - model: mistralai/Mistral-7B-v0.1
+    # no parameters necessary for base model
+  - model: mlabonne/OmniTruthyBeagle-7B-v0
+    parameters:
+      density: 0.60
+      weight: 0.30
+  - model: mayflowergmbh/Wiedervereinigung-7b-dpo-laser
+    parameters:
+      density: 0.65
+      weight: 0.40
+  - model: cognitivecomputations/openchat-3.5-0106-laser
+    parameters:
+      density: 0.6
+      weight: 0.3
+merge_method: dare_ties
+base_model: mistralai/Mistral-7B-v0.1
+parameters:
+  int8_mask: true
+dtype: bfloat16
+random_seed: 0
+```
+
+## 📈 Mt-Bench-De
+```json
+{
+    "first_turn": 7.8875,
+    "second_turn": 7.31875,
+    "categories": {
+        "writing": 8.65,
+        "roleplay": 8.225,
+        "reasoning": 6.5,
+        "math": 4.55,
+        "coding": 6.1,
+        "extraction": 8.25,
+        "stem": 9.2,
+        "humanities": 9.35
+    },
+    "average": 7.603125
+}
+```
+
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "johannhartmann/Wiederchat-7b-dpo-laser"
+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"])
+```