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README.md

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+---
+tags:
+- merge
+- mergekit
+- lazymergekit
+- aaditya/Llama3-OpenBioLLM-8B
+- johnsnowlabs/JSL-MedLlama-3-8B-v2.0
+- Jayant9928/orpo_med_v3
+- skumar9/Llama-medx_v3
+base_model:
+- aaditya/Llama3-OpenBioLLM-8B
+- johnsnowlabs/JSL-MedLlama-3-8B-v2.0
+- Jayant9928/orpo_med_v3
+- skumar9/Llama-medx_v3
+---
+
+# Llama-3-OpenBioMed-8B-dare-ties-4x
+
+Llama-3-OpenBioMed-8B-dare-ties-4x is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+* [aaditya/Llama3-OpenBioLLM-8B](https://huggingface.co/aaditya/Llama3-OpenBioLLM-8B)
+* [johnsnowlabs/JSL-MedLlama-3-8B-v2.0](https://huggingface.co/johnsnowlabs/JSL-MedLlama-3-8B-v2.0)
+* [Jayant9928/orpo_med_v3](https://huggingface.co/Jayant9928/orpo_med_v3)
+* [skumar9/Llama-medx_v3](https://huggingface.co/skumar9/Llama-medx_v3)
+
+## 🧩 Configuration
+
+```yaml
+models:
+  - model: johnsnowlabs/JSL-MedLlama-3-8B-v2.0
+    # No parameters necessary for base model
+  - model: aaditya/Llama3-OpenBioLLM-8B
+    parameters:
+      density: 0.53
+      weight: 0.2
+  - model: johnsnowlabs/JSL-MedLlama-3-8B-v2.0
+    parameters:
+      density: 0.53
+      weight: 0.3
+  - model: Jayant9928/orpo_med_v3
+    parameters:
+      density: 0.53
+      weight: 0.3
+  - model: skumar9/Llama-medx_v3
+    parameters:
+        density: 0.53
+        weight: 0.2
+merge_method: dare_ties
+base_model: meta-llama/Meta-Llama-3-8B-Instruct
+parameters:
+  int8_mask: true
+dtype: bfloat16
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "abhinand/Llama-3-OpenBioMed-8B-dare-ties-4x"
+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"])
+```