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.gitattributes

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+neuralgemma-2b-slerp.Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+base_model:
+- google/gemma-2-2b-it
+- Kukedlc/Gemma-2-2B-Spanish-1.0
+tags:
+- merge
+- mergekit
+- lazymergekit
+- google/gemma-2-2b-it
+- Kukedlc/Gemma-2-2B-Spanish-1.0
+- autoquant
+- gguf
+---
+
+# NeuralGemma-2B-Slerp
+
+NeuralGemma-2B-Slerp is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+* [google/gemma-2-2b-it](https://huggingface.co/google/gemma-2-2b-it)
+* [Kukedlc/Gemma-2-2B-Spanish-1.0](https://huggingface.co/Kukedlc/Gemma-2-2B-Spanish-1.0)
+
+## 🧩 Configuration
+
+```yaml
+models:
+  - model: google/gemma-2-2b
+    # No parameters necessary for base model
+  - model: google/gemma-2-2b-it
+    parameters:
+      density: 0.55
+      weight: 0.6
+  - model: Kukedlc/Gemma-2-2B-Spanish-1.0
+    parameters:
+      density: 0.55
+      weight: 0.4
+merge_method: dare_ties
+base_model: google/gemma-2-2b
+parameters:
+  int8_mask: true
+dtype: float16
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "Kukedlc/NeuralGemma-2B-Slerp"
+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"])
+```

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