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Model: saucam/mistral-orpo-beta-NeuralBeagle14-7B-dare-ties
Source: Original Platform

README.md

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+---
+tags:
+- merge
+- mergekit
+- lazymergekit
+- kaist-ai/mistral-orpo-beta
+- mlabonne/NeuralBeagle14-7B
+base_model:
+- kaist-ai/mistral-orpo-beta
+- mlabonne/NeuralBeagle14-7B
+license: apache-2.0
+---
+
+# mistral-orpo-beta-NeuralBeagle14-7B-dare-ties
+
+mistral-orpo-beta-NeuralBeagle14-7B-dare-ties is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+* [kaist-ai/mistral-orpo-beta](https://huggingface.co/kaist-ai/mistral-orpo-beta)
+* [mlabonne/NeuralBeagle14-7B](https://huggingface.co/mlabonne/NeuralBeagle14-7B)
+
+## 🧩 Configuration
+
+```yaml
+models:
+  - model: kaist-ai/mistral-orpo-beta
+    parameters:
+      density: 0.5
+      weight: 0.6
+    # No parameters necessary for base model
+  - model: mlabonne/NeuralBeagle14-7B
+    parameters:
+      density: 0.5
+      weight: 0.4
+merge_method: dare_ties
+base_model: kaist-ai/mistral-orpo-beta
+parameters:
+  int8_mask: true
+dtype: bfloat16
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "saucam/mistral-orpo-beta-NeuralBeagle14-7B-dare-ties"
+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"])
+```
+
+Evaluation results for openllm benchmark via [llm-autoeval](https://github.com/mlabonne/llm-autoeval)
+
+https://gist.github.com/saucam/dcc1f43acce8179f476afc2d91be53ff