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README.md

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+Quantization made by Richard Erkhov.
+
+[Github](https://github.com/RichardErkhov)
+
+[Discord](https://discord.gg/pvy7H8DZMG)
+
+[Request more models](https://github.com/RichardErkhov/quant_request)
+
+
+KangalKhan-RawRuby-7B - bnb 8bits
+- Model creator: https://huggingface.co/Yuma42/
+- Original model: https://huggingface.co/Yuma42/KangalKhan-RawRuby-7B/
+
+
+
+
+Original model description:
+---
+language:
+- en
+license: apache-2.0
+tags:
+- merge
+- mergekit
+- lazymergekit
+- Yuma42/KangalKhan-Ruby-7B-Fixed
+- Yuma42/KangalKhan-RawEmerald-7B
+base_model:
+- Yuma42/KangalKhan-Ruby-7B-Fixed
+- Yuma42/KangalKhan-RawEmerald-7B
+model-index:
+- name: KangalKhan-RawRuby-7B
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: AI2 Reasoning Challenge (25-Shot)
+      type: ai2_arc
+      config: ARC-Challenge
+      split: test
+      args:
+        num_few_shot: 25
+    metrics:
+    - type: acc_norm
+      value: 66.89
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Yuma42/KangalKhan-RawRuby-7B
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: HellaSwag (10-Shot)
+      type: hellaswag
+      split: validation
+      args:
+        num_few_shot: 10
+    metrics:
+    - type: acc_norm
+      value: 85.53
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Yuma42/KangalKhan-RawRuby-7B
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU (5-Shot)
+      type: cais/mmlu
+      config: all
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 63.46
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Yuma42/KangalKhan-RawRuby-7B
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: TruthfulQA (0-shot)
+      type: truthful_qa
+      config: multiple_choice
+      split: validation
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: mc2
+      value: 57.09
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Yuma42/KangalKhan-RawRuby-7B
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: Winogrande (5-shot)
+      type: winogrande
+      config: winogrande_xl
+      split: validation
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 78.69
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Yuma42/KangalKhan-RawRuby-7B
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GSM8k (5-shot)
+      type: gsm8k
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 62.02
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Yuma42/KangalKhan-RawRuby-7B
+      name: Open LLM Leaderboard
+---
+
+# KangalKhan-RawRuby-7B
+
+I suggest using ChatML (Use whatever system prompt you like, this is just an example!):
+```
+<|im_start|>system
+You are a friendly assistant.<|im_end|>
+<|im_start|>user
+Hello, what are you?<|im_end|>
+<|im_start|>assistant
+I am an AI language model designed to assist users with information and answer their questions. How can I help you today?<|im_end|>
+```
+
+
+Q4_K_S GGUF:  
+https://huggingface.co/Yuma42/KangalKhan-RawRuby-7B-GGUF  
+
+More GGUF variants by [mradermacher](https://huggingface.co/mradermacher):  
+WARNING: I have observed that these versions output typos in rare cases. If you have the same problem, use my Q4_K_S GGUF above.
+https://huggingface.co/mradermacher/KangalKhan-RawRuby-7B-GGUF
+weighted/imatrix GGUF by [mradermacher](https://huggingface.co/mradermacher):  
+https://huggingface.co/mradermacher/KangalKhan-RawRuby-7B-i1-GGUF
+
+
+
+KangalKhan-RawRuby-7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+* [Yuma42/KangalKhan-Ruby-7B-Fixed](https://huggingface.co/Yuma42/KangalKhan-Ruby-7B-Fixed)
+* [Yuma42/KangalKhan-RawEmerald-7B](https://huggingface.co/Yuma42/KangalKhan-RawRuby-7B)
+
+## 🧩 Configuration
+
+```yaml
+slices:
+  - sources:
+      - model: Yuma42/KangalKhan-Ruby-7B-Fixed
+        layer_range: [0, 32]
+      - model: Yuma42/KangalKhan-RawEmerald-7B
+        layer_range: [0, 32]
+merge_method: slerp
+base_model: Yuma42/KangalKhan-Ruby-7B-Fixed
+parameters:
+  t:
+    - filter: self_attn
+      value: [0.1, 0.55, 0.35, 0.75, 0.97]
+    - filter: mlp
+      value: [0.9, 0.45, 0.65, 0.25, 0.03]
+    - value: 0.5
+dtype: bfloat16
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "Yuma42/KangalKhan-RawRuby-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"])
+```
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Yuma42__KangalKhan-RawRuby-7B)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |68.95|
+|AI2 Reasoning Challenge (25-Shot)|66.89|
+|HellaSwag (10-Shot)              |85.53|
+|MMLU (5-Shot)                    |63.46|
+|TruthfulQA (0-shot)              |57.09|
+|Winogrande (5-shot)              |78.69|
+|GSM8k (5-shot)                   |62.02|
+
+
+