Create README.md

README.md

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+---
+base_model:
+- Dampfinchen/Llama-3.1-8B-Ultra-Instruct
+tags:
+- merge
+- mergekit
+- Undi95/Meta-Llama-3.1-8B-Claude
+- Dampfinchen/Llama-3.1-8B-Ultra-Instruct
+license: llama3.1
+language:
+- en
+- de
+---
+
+# llama3.1-8b-spaetzle-v59
+
+llama3.1-8b-spaetzle-v59 is a dare ties merge of the models 
+* [Undi95/Meta-Llama-3.1-8B-Claude](https://huggingface.co/Undi95/Meta-Llama-3.1-8B-Claude)
+* [Dampfinchen/Llama-3.1-8B-Ultra-Instruct](https://huggingface.co/Dampfinchen/Llama-3.1-8B-Ultra-Instruct)
+
+## 🧩 Configuration
+
+```yaml
+models:
+  - model: Dampfinchen/Llama-3.1-8B-Ultra-Instruct
+    # no parameters necessary for base model
+  - model: Undi95/Meta-Llama-3.1-8B-Claude
+    parameters:
+      density: 0.65
+      weight: 0.4
+merge_method: dare_ties
+base_model: Dampfinchen/Llama-3.1-8B-Ultra-Instruct
+parameters:
+  int8_mask: true
+dtype: bfloat16
+random_seed: 0
+tokenizer_source: base
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "cstr/llama3.1-8b-spaetzle-v59"
+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"])
+```