Create README.md

README.md

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+---
+tags:
+- merge
+- mergekit
+- lazymergekit
+- SanjiWatsuki/Silicon-Maid-7B
+- chargoddard/loyal-piano-m7-cdpo
+- jsfs11/RandomMergeNoNormWEIGHTED-7B-DARETIES
+- NeverSleep/Noromaid-7b-v0.2
+- athirdpath/NSFW_DPO_vmgb-7b
+base_model:
+- SanjiWatsuki/Silicon-Maid-7B
+- chargoddard/loyal-piano-m7-cdpo
+- jsfs11/RandomMergeNoNormWEIGHTED-7B-DARETIES
+- NeverSleep/Noromaid-7b-v0.2
+- athirdpath/NSFW_DPO_vmgb-7b
+---
+
+# HighdensityRPMerge-7B
+
+HighdensityRPMerge-7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+* [SanjiWatsuki/Silicon-Maid-7B](https://huggingface.co/SanjiWatsuki/Silicon-Maid-7B)
+* [chargoddard/loyal-piano-m7-cdpo](https://huggingface.co/chargoddard/loyal-piano-m7-cdpo)
+* [jsfs11/RandomMergeNoNormWEIGHTED-7B-DARETIES](https://huggingface.co/jsfs11/RandomMergeNoNormWEIGHTED-7B-DARETIES)
+* [NeverSleep/Noromaid-7b-v0.2](https://huggingface.co/NeverSleep/Noromaid-7b-v0.2)
+* [athirdpath/NSFW_DPO_vmgb-7b](https://huggingface.co/athirdpath/NSFW_DPO_vmgb-7b)
+
+## 🧩 Configuration
+
+```yaml
+models:
+  - model: saishf/West-Hermes-7B
+    # no parameters necessary for base model
+  - model: SanjiWatsuki/Silicon-Maid-7B
+    parameters:
+      weight: 0.4
+      density: 0.8
+  - model: chargoddard/loyal-piano-m7-cdpo
+    parameters:
+      weight: 0.3
+      density: 0.8
+  - model: jsfs11/RandomMergeNoNormWEIGHTED-7B-DARETIES
+    parameters:
+      weight: 0.25
+      density: 0.45
+  - model: NeverSleep/Noromaid-7b-v0.2
+    parameters:
+      weight: 0.25
+      density: 0.4
+  - model: athirdpath/NSFW_DPO_vmgb-7b
+    parameters:
+      weight: 0.2
+      density: 0.4
+merge_method: dare_ties
+base_model: saishf/West-Hermes-7B
+parameters:
+  int8_mask: true
+dtype: bfloat16
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "jsfs11/HighdensityRPMerge-7B"
+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"])
+```