Create README.md

README.md

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+---
+base_model:
+- cstr/llama3.1-8b-spaetzle-v59
+- cstr/llama3.1-8b-spaetzle-v63
+- cstr/llama3.1-8b-spaetzle-v66
+- cstr/llama3.1-8b-spaetzle-v73
+tags:
+- merge
+- mergekit
+license: llama3
+language:
+- en
+- de
+library_name: transformers
+---
+
+# llama3.1-8b-spaetzle-v74
+
+llama3.1-8b-spaetzle-v74 is a merge of the following models:
+* [cstr/llama3.1-8b-spaetzle-v59](https://huggingface.co/cstr/llama3.1-8b-spaetzle-v59)
+* [cstr/llama3.1-8b-spaetzle-v63](https://huggingface.co/cstr/llama3.1-8b-spaetzle-v63)
+* [cstr/llama3.1-8b-spaetzle-v66](https://huggingface.co/cstr/llama3.1-8b-spaetzle-v66)
+* [cstr/llama3.1-8b-spaetzle-v73](https://huggingface.co/cstr/llama3.1-8b-spaetzle-v73)
+
+EQ-Bench v2_de: 68.05 169/171, en: 75.27 - which is not the best, but it produces decent answers for some trick questions, and i have a sweet spot for that ;)
+
+## 🧩 Configuration
+
+```yamlmodels:
+models:
+  - model: cstr/llama3.1-8b-spaetzle-v59
+    parameters:
+      weight: 0.3
+      density: 0.5
+  - model: cstr/llama3.1-8b-spaetzle-v63
+    parameters:
+      weight: 0.15
+      density: 0.5
+  - model: cstr/llama3.1-8b-spaetzle-v66
+    parameters:
+      weight: 0.15
+      density: 0.5
+  - model: cstr/llama3.1-8b-spaetzle-v73
+    parameters:
+      weight: 0.4
+      density: 0.5
+base_model: cstr/llama3.1-8b-spaetzle-v59
+merge_method: della_linear
+parameters:
+  int8_mask: true
+  normalize: true
+  epsilon: 0.1  
+  lambda: 1.0   
+  density: 0.7
+dtype: bfloat16
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "cstr/llama3.1-8b-spaetzle-v74"
+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"])
+```